Typology
operator:
and / or
Language
operator:
and / or
Date
operator:
and / or
Rights
operator:
and / or
2014
Report
Open Access
WP1-CNR-ISTI - Ricostruzione di reti di regolazione genica da dati trascrittomici
Caudai C.
Some recently proposed approaches to identify genetic regulatory mechanisms from sequencing experiments are briefly described. Since gene expression is influenced by biologica processes in the cell, and both the processes and the related transcription factors are largely unknown, many attempts have been made to solve this problem by blind source separation techniques. We analyse some of these approaches, each based on a linear data model.Source: Project report, Bandiera InterOmics, 2014
Caudai C.
Some recently proposed approaches to identify genetic regulatory mechanisms from sequencing experiments are briefly described. Since gene expression is influenced by biologica processes in the cell, and both the processes and the related transcription factors are largely unknown, many attempts have been made to solve this problem by blind source separation techniques. We analyse some of these approaches, each based on a linear data model.Source: Project report, Bandiera InterOmics, 2014
See at:
ISTI Repository 
| CNR ExploRA
2014
Report
Open Access
Ricostruzione tridimensionale della struttura della cromatina da dati tipo Chromosome Conformation Capture. Nota riservata, progetto InterOmics
Caudai C.
This document reports part of the WP1-ISTI unit activity in the framework of the national Flagship Project InterOmics, on the 3D chromatin structure analysis from Hi-C experiments. Compared with other methods presented in the literature, our approach uses a new solution model incorporating sound prior knowledge, and a new reconstruction criterion that does not require an explicit translation of the Hi-C data into Euclidean distances between pairs of genomic loci. This approach also allows us to solve the problem in a multiscale setting, by reconstructing significant fragments separately at high resolution and then putting them together through the same criterion applied to lower-resolution data.Source: Project report, Bandiera InterOmics, 2014
Caudai C.
This document reports part of the WP1-ISTI unit activity in the framework of the national Flagship Project InterOmics, on the 3D chromatin structure analysis from Hi-C experiments. Compared with other methods presented in the literature, our approach uses a new solution model incorporating sound prior knowledge, and a new reconstruction criterion that does not require an explicit translation of the Hi-C data into Euclidean distances between pairs of genomic loci. This approach also allows us to solve the problem in a multiscale setting, by reconstructing significant fragments separately at high resolution and then putting them together through the same criterion applied to lower-resolution data.Source: Project report, Bandiera InterOmics, 2014
See at:
ISTI Repository | CNR ExploRA
2016
Journal article
Open Access
Computational estimation of chromosome structure
Caudai C., Salerno E.
Research performed at ISTI-CNR in the framework of the national Flagship Project InterOmics includes the development of algorithms to reconstruct the chromosome structure from "chromosome conformation capture" data. One algorithm now being tested has already produced interesting results. Unlike most popular techniques, it does not derive a classical distance-to-geometry problem from the original contact data, and applies an efficient multiresolution approach to the genome under study.Source: ERCIM news 104 (2016): 21–22.
Caudai C., Salerno E.
Research performed at ISTI-CNR in the framework of the national Flagship Project InterOmics includes the development of algorithms to reconstruct the chromosome structure from "chromosome conformation capture" data. One algorithm now being tested has already produced interesting results. Unlike most popular techniques, it does not derive a classical distance-to-geometry problem from the original contact data, and applies an efficient multiresolution approach to the genome under study.Source: ERCIM news 104 (2016): 21–22.
See at:
ercim-news.ercim.eu | CNR ExploRA
2016
Software
Unknown
Reconstruction of 3D chromatin structure from chromosome conformation capture data (Release 2.0)
Salerno E., Caudai C.
This Python code provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. The related genomic resolution, along with a few geometric parameters and the parameters for tuning the estimation algorithm must be set in advance in a special section of the source code. The whole fibre is divided in independent segments, whose structures are estimated and modelled as single elements of a lower-resolution fibre that is treated recursively in the same way, until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another recursive procedure.
Salerno E., Caudai C.
This Python code provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. The related genomic resolution, along with a few geometric parameters and the parameters for tuning the estimation algorithm must be set in advance in a special section of the source code. The whole fibre is divided in independent segments, whose structures are estimated and modelled as single elements of a lower-resolution fibre that is treated recursively in the same way, until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another recursive procedure.
See at: CNR ExploRA
2016
Software
Unknown
Reconstruction of 3D chromatin structure from chromosome conformation capture data (Release 3.1)
Salerno E., Caudai C.
This Python code has a command-line and a GUI versions, and provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. In the command-line version, the related genomic resolution, along with a few geometric parameters and the parameters for tuning the estimation algorithm must be set in advance in a special section of the source code. In the GUI version, all the tuneable parameters are made available in the user interface. The whole fibre is divided in independent segments, whose structures are estimated and modelled as single elements of a lower-resolution fibre that is treated recursively in the same way, until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another recursive procedure. See the Readme file and the cited references for more detail.DOI: 10.13140/rg.2.2.35785.13923
Metrics:
Salerno E., Caudai C.
This Python code has a command-line and a GUI versions, and provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. In the command-line version, the related genomic resolution, along with a few geometric parameters and the parameters for tuning the estimation algorithm must be set in advance in a special section of the source code. In the GUI version, all the tuneable parameters are made available in the user interface. The whole fibre is divided in independent segments, whose structures are estimated and modelled as single elements of a lower-resolution fibre that is treated recursively in the same way, until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another recursive procedure. See the Readme file and the cited references for more detail.DOI: 10.13140/rg.2.2.35785.13923
Metrics:
See at: CNR ExploRA
2018
Software
Unknown
ChromStruct v4.2 - Reconstruction of 3D chromatin structure from chromosome conformation capture data
Salerno E., Caudai C.
This Python (v.2.7.10) code provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. The code features a GUI where all the tuneable parameters are made available to the user. The fibre is divided in independent segments whose structures are first estimated separately and then modelled as single elements of a lower-resolution fibre, which is treated iteratively in the same way until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another iterative procedure. See the Readme file and the cited references for more detail.
Salerno E., Caudai C.
This Python (v.2.7.10) code provides an estimate of the 3D structure of the chromatin fibre in cell nuclei from the contact frequency data produced by a 'Chromosome conformation capture' experiment. The only input required is a text file containing a general real matrix of contact frequencies. The code features a GUI where all the tuneable parameters are made available to the user. The fibre is divided in independent segments whose structures are first estimated separately and then modelled as single elements of a lower-resolution fibre, which is treated iteratively in the same way until it cannot be divided anymore into independent segments. The full-resolution chain is then reconstructed by another iterative procedure. See the Readme file and the cited references for more detail.
See at: CNR ExploRA | www.researchgate.net
2015
Report
Open Access
Architettura ISTI per il progetto INTEROMICS
Caudai C., Righi M., Tampucci M.
Il progetto INTEROMICS (Sviluppo di una piattaforma integrata per l'applicazione delle scienze "omiche" alla definizione dei biomarcatori e profili diagnostici, predittivi e teranostici) prevede lo sviluppo delle competenze per l'intera filiera delle "scienze omiche", con particolare riferimento alla genomica, proteomica, bioinformatica e system biology. Il laboratorio concentra le sue attività nel campo della bioinformatica e dell'analisi delle immagini per impieghi in biologia.Source: ISTI Technical reports, 2015
Caudai C., Righi M., Tampucci M.
Il progetto INTEROMICS (Sviluppo di una piattaforma integrata per l'applicazione delle scienze "omiche" alla definizione dei biomarcatori e profili diagnostici, predittivi e teranostici) prevede lo sviluppo delle competenze per l'intera filiera delle "scienze omiche", con particolare riferimento alla genomica, proteomica, bioinformatica e system biology. Il laboratorio concentra le sue attività nel campo della bioinformatica e dell'analisi delle immagini per impieghi in biologia.Source: ISTI Technical reports, 2015
See at:
ISTI Repository | CNR ExploRA
2014
Contribution to conference
Open Access
A statistical approach to infer 3D chromatin structure
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Our goal in the framework of the Italian Flagship Project InterOmics is to reconstruct a set of plausible chromatin configurations from Chromosome Conformation Capture data. To this end, we rely on a simulated annealing algorithm that samples the solution space defined by a data-fit function and a multiscale chromatin model. The data-fit only accounts for the largest, most reliable contact frequencies, in order to avoid deriving distances inconsistent with the Euclidean geometry. At each scale, the chromatin model consists in a chain of partially penetrable beads whose properties (bead sizes, elasticity, curvature, etc.) can be constrained through biochemical and biological knowledge. During the annealing process, the model configuration is evolved through quaternions rather than the usual Euler matrices, as this offers a number of advantages in terms of composition of successive perturbations and automatic satisfaction of the constraints. The output of the annealing scheme is not unique due to the degrees of freedom left by the geometrical constraints. This allows us to obtain multiple configurations compatible with both the data and the prior knowledge. We are validating our method by applying it to real Hi-C data from the long arm of the human Chromosome 1. The mean-square Euclidean distances computed from our results as functions of the genomic distances support previous experimental results indicating that highly expressed genomic regions are less compact than poorly transcribed regions.Source: BMTL 2014 - Bringing Maths to Life, pp. 42–42, Napoli, Italia, 27-29 ottobre 2014
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Our goal in the framework of the Italian Flagship Project InterOmics is to reconstruct a set of plausible chromatin configurations from Chromosome Conformation Capture data. To this end, we rely on a simulated annealing algorithm that samples the solution space defined by a data-fit function and a multiscale chromatin model. The data-fit only accounts for the largest, most reliable contact frequencies, in order to avoid deriving distances inconsistent with the Euclidean geometry. At each scale, the chromatin model consists in a chain of partially penetrable beads whose properties (bead sizes, elasticity, curvature, etc.) can be constrained through biochemical and biological knowledge. During the annealing process, the model configuration is evolved through quaternions rather than the usual Euler matrices, as this offers a number of advantages in terms of composition of successive perturbations and automatic satisfaction of the constraints. The output of the annealing scheme is not unique due to the degrees of freedom left by the geometrical constraints. This allows us to obtain multiple configurations compatible with both the data and the prior knowledge. We are validating our method by applying it to real Hi-C data from the long arm of the human Chromosome 1. The mean-square Euclidean distances computed from our results as functions of the genomic distances support previous experimental results indicating that highly expressed genomic regions are less compact than poorly transcribed regions.Source: BMTL 2014 - Bringing Maths to Life, pp. 42–42, Napoli, Italia, 27-29 ottobre 2014
See at:
www.bmtl.it | CNR ExploRA
2014
Contribution to conference
Open Access
A multiscale model for 3D chromatin structure estimation using quaternions
Caudai C., Salerno E., Zoppè M., Tonazzini A.
We present a method to reconstruct a set of plausible chromatin configurations from contact data obtained through Chromosome Conformation Capture techniques. We do not look for a unique configuration because the experimental data are not derived from a single cell, but from millions of cells. As opposed to most popular methods, we do not translate contact frequencies deterministically into distances, since this often produces structures that are not consistent with the Euclidean geometry. We build a data-fit function directly from the pairs of loci with the largest contact frequencies, assuming that they are likely to be in contact, and neglecting the pairs with very low or zero contact frequencies, as we cannot infer anything about their mutual distances. To obtain configurations consistent with both the data and the available biological knowledge, we introduce a chromatin model that can be suitably constrained. Taking advantage of the block structure of the contact matrix, we adopt a multiscale approach where the chromatin fiber is divided into a number of segments that can be treated in parallel. Each of them is modeled as a chain of partially penetrable beads whose properties (bead sizes, elasticity, curvature, etc.) can be constrained on the basis of biochemical and biological knowledge. The model parameters can easily be extended to exploit any further information available. Once the individual structures are reconstructed, each segment can be treated as an element of a new chain, and the procedure can be repeated recursively at different scales. Our algorithm samples the solution space generated by the data-fit function through a Monte Carlo method. At each step, the subchains are perturbed by using quaternions. This is an extension of the complex algebra that offers a number of advantages, by avoiding singularities typical in the Euler matrix formalism, facilitating the composition of rotations, and allowing for a continuous evolution of the structure that is intrinsically compatible with the topological constraints. To validate the new method, we applied it to real Hi-C data available online (Lieberman-Aiden et al., 2009). In particular, we analyzed the contact frequency data from the long arm of the human Chromosome 1 with a maximum resolution of 100 kb, obtaining a number of output configurations. For each configuration, the first division of the overall fiber included 25 topological domains (Dixon et al., 2012). The reconstructed structures were then assumed as single elements of a new chain (with nonuniform resolution), whose mutual interactions were estimated by the same algorithm. The output structures should be validated biologically. As a first test, we computed the relationships between the genomic and Euclidean distances of pairs of loci in the entire chains reconstructed. Our results are compatible with the analogous plots, derived from FISH experiments on the same genomic region, found in Mateos-Langerak et al. (2009).Source: ECCB 2014 - 13th European Conference on Computational Biology, Strasbourg, France, 7-10 September 2014
Caudai C., Salerno E., Zoppè M., Tonazzini A.
We present a method to reconstruct a set of plausible chromatin configurations from contact data obtained through Chromosome Conformation Capture techniques. We do not look for a unique configuration because the experimental data are not derived from a single cell, but from millions of cells. As opposed to most popular methods, we do not translate contact frequencies deterministically into distances, since this often produces structures that are not consistent with the Euclidean geometry. We build a data-fit function directly from the pairs of loci with the largest contact frequencies, assuming that they are likely to be in contact, and neglecting the pairs with very low or zero contact frequencies, as we cannot infer anything about their mutual distances. To obtain configurations consistent with both the data and the available biological knowledge, we introduce a chromatin model that can be suitably constrained. Taking advantage of the block structure of the contact matrix, we adopt a multiscale approach where the chromatin fiber is divided into a number of segments that can be treated in parallel. Each of them is modeled as a chain of partially penetrable beads whose properties (bead sizes, elasticity, curvature, etc.) can be constrained on the basis of biochemical and biological knowledge. The model parameters can easily be extended to exploit any further information available. Once the individual structures are reconstructed, each segment can be treated as an element of a new chain, and the procedure can be repeated recursively at different scales. Our algorithm samples the solution space generated by the data-fit function through a Monte Carlo method. At each step, the subchains are perturbed by using quaternions. This is an extension of the complex algebra that offers a number of advantages, by avoiding singularities typical in the Euler matrix formalism, facilitating the composition of rotations, and allowing for a continuous evolution of the structure that is intrinsically compatible with the topological constraints. To validate the new method, we applied it to real Hi-C data available online (Lieberman-Aiden et al., 2009). In particular, we analyzed the contact frequency data from the long arm of the human Chromosome 1 with a maximum resolution of 100 kb, obtaining a number of output configurations. For each configuration, the first division of the overall fiber included 25 topological domains (Dixon et al., 2012). The reconstructed structures were then assumed as single elements of a new chain (with nonuniform resolution), whose mutual interactions were estimated by the same algorithm. The output structures should be validated biologically. As a first test, we computed the relationships between the genomic and Euclidean distances of pairs of loci in the entire chains reconstructed. Our results are compatible with the analogous plots, derived from FISH experiments on the same genomic region, found in Mateos-Langerak et al. (2009).Source: ECCB 2014 - 13th European Conference on Computational Biology, Strasbourg, France, 7-10 September 2014
See at:
www.eccb14.org | CNR ExploRA
2015
Report
Open Access
InterOmics - Reconstructing 3D chromatin structure from chromosome conformation capture data.
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Dna is the central repository of information to keep cells and organisms alive. In human cells, the 46 chromosomes amount to a length of about 2 m, with a diameter of 2 nm, and are packed in a way that allows for access by transcription, replication and repair machinery, fitting within a globular nucleus with a radius of 5000 to 10000 nm. Efficiency of packing is obtained by several levels of packing mechanisms (Figure 1), both general (due to general principles, irrespective of Dna sequence) and speci fic, i.e. mediated by proteins that recognize specifi c motives (sequences) and bring in close proximity parts of Dna that may be very distant in the genomic sequence. In both cases, general packing and specifi c aggregation, the underlying mechanisms are not entirely described or understood. The fi rst level, mediated by histon octamers, produces a ber of 11 nm, which in turn is organized into a 30 nm-wide structure. Further packing is at work in cells, and the research community engaged in the study of chromatin conformation is producing increasing knowledge that will finally allow for a clear vision of the nuclear machinery that regulates Dna metabolism.Source: Project report, InterOmics, 2015
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Dna is the central repository of information to keep cells and organisms alive. In human cells, the 46 chromosomes amount to a length of about 2 m, with a diameter of 2 nm, and are packed in a way that allows for access by transcription, replication and repair machinery, fitting within a globular nucleus with a radius of 5000 to 10000 nm. Efficiency of packing is obtained by several levels of packing mechanisms (Figure 1), both general (due to general principles, irrespective of Dna sequence) and speci fic, i.e. mediated by proteins that recognize specifi c motives (sequences) and bring in close proximity parts of Dna that may be very distant in the genomic sequence. In both cases, general packing and specifi c aggregation, the underlying mechanisms are not entirely described or understood. The fi rst level, mediated by histon octamers, produces a ber of 11 nm, which in turn is organized into a 30 nm-wide structure. Further packing is at work in cells, and the research community engaged in the study of chromatin conformation is producing increasing knowledge that will finally allow for a clear vision of the nuclear machinery that regulates Dna metabolism.Source: Project report, InterOmics, 2015
See at:
ISTI Repository | CNR ExploRA
2015
Journal article
Open Access
Inferring 3D chromatin structure using a multiscale approach based on quaternions
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Background: The knowledge of the spatial organisation of the chromatin fibre in cell nuclei helps researchers to understand the nuclear machinery that regulates DNA activity. Recent experimental techniques of the type Chromosome Conformation Capture (3C, or similar) provide high-resolution, high-throughput data consisting in the number of times any possible pair of textsc{dna} fragments is found to be in contact, in a certain population of cells. As these data carry information on the structure of the chromatin fibre, several attempts have been made to use them to obtain high-resolution 3D reconstructions of entire chromosomes, or even an entire genome. The techniques proposed treat the data in different ways, possibly exploiting physical-geometric chromatin models. One popular strategy is to transform contact data into Euclidean distances between pairs of fragments, and then solve a classical distance-to-geometry problem. Results: We developed and tested a reconstruction technique that does not require translating contacts into distances, thus avoiding a number of related drawbacks. Also, we introduce a geometrical chromatin chain model that allows us to include sound biochemical and biological constraints in the problem. This model can be scaled at different genomic resolutions, where the structures of the coarser models are influenced by the reconstructions at finer resolutions. The search in the solution space is then performed by a classical simulated annealing, where the model is evolved efficiently through quaternion operators. The presence of appropriate constraints permits the less reliable data to be overlooked, so the result is a set of plausible chromatin configurations compatible with both the data and the prior knowledge. Conclusions: To test our method, we obtained a number of 3D chromatin configurations from Hi-C data available in the literature for the long arm of human chromosome 1, and validated their features against known properties of gene density and transcriptional activity. Our results are compatible with biological features not introduced {em a priori} in the problem: structurally different regions in our reconstructions highly correlate with functionally different regions as known from literature and genomic repositories.Source: BMC bioinformatics 16 (2015). doi:10.1186/s12859-015-0667-0
DOI: 10.1186/s12859-015-0667-0
Metrics:
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Background: The knowledge of the spatial organisation of the chromatin fibre in cell nuclei helps researchers to understand the nuclear machinery that regulates DNA activity. Recent experimental techniques of the type Chromosome Conformation Capture (3C, or similar) provide high-resolution, high-throughput data consisting in the number of times any possible pair of textsc{dna} fragments is found to be in contact, in a certain population of cells. As these data carry information on the structure of the chromatin fibre, several attempts have been made to use them to obtain high-resolution 3D reconstructions of entire chromosomes, or even an entire genome. The techniques proposed treat the data in different ways, possibly exploiting physical-geometric chromatin models. One popular strategy is to transform contact data into Euclidean distances between pairs of fragments, and then solve a classical distance-to-geometry problem. Results: We developed and tested a reconstruction technique that does not require translating contacts into distances, thus avoiding a number of related drawbacks. Also, we introduce a geometrical chromatin chain model that allows us to include sound biochemical and biological constraints in the problem. This model can be scaled at different genomic resolutions, where the structures of the coarser models are influenced by the reconstructions at finer resolutions. The search in the solution space is then performed by a classical simulated annealing, where the model is evolved efficiently through quaternion operators. The presence of appropriate constraints permits the less reliable data to be overlooked, so the result is a set of plausible chromatin configurations compatible with both the data and the prior knowledge. Conclusions: To test our method, we obtained a number of 3D chromatin configurations from Hi-C data available in the literature for the long arm of human chromosome 1, and validated their features against known properties of gene density and transcriptional activity. Our results are compatible with biological features not introduced {em a priori} in the problem: structurally different regions in our reconstructions highly correlate with functionally different regions as known from literature and genomic repositories.Source: BMC bioinformatics 16 (2015). doi:10.1186/s12859-015-0667-0
DOI: 10.1186/s12859-015-0667-0
Metrics:
See at:
BMC Bioinformatics | BMC Bioinformatics | BMC Bioinformatics | ISTI Repository | www.biomedcentral.com | CNR ExploRA
2015
Contribution to book
Open Access
A statistical approach to infer 3D chromatin structure
Caudai C., Salerno E., Zoppé M., Tonazzini A.
We propose a new algorithm to estimate the 3D configuration of a chromatin chain from the contact frequency data provided by HI-C experiments. Since the data originate from a population of cells, we rather aim at obtaining a set of structures that are compatible with both the data and our prior knowledge. Our method overcomes some drawbacks presented by other state-of-the-art methods, including the problems related to the translation of contact frequencies into Euclidean distances. Indeed, such a translation always produces a geometrically inconsistent distance set. Our multiscale chromatin model and our probabilistic solution approach allow us to partition the problem, thus speeding up the solution, to include suitable constraints, and to get multiple feasible structures. Moreover, the density function we use to sample the solution space does not require any translation from contact frequencies into distances.Source: Mathematical Models in Biology. Bringing Mathematics to Life, edited by Valeria Zazzu, Maria Brigida Ferraro, Mario R. Guarracino, pp. 161–171. Berlin Heidelberg: Springer, 2015
DOI: 10.1007/978-3-319-23497-7_12
Metrics:
Caudai C., Salerno E., Zoppé M., Tonazzini A.
We propose a new algorithm to estimate the 3D configuration of a chromatin chain from the contact frequency data provided by HI-C experiments. Since the data originate from a population of cells, we rather aim at obtaining a set of structures that are compatible with both the data and our prior knowledge. Our method overcomes some drawbacks presented by other state-of-the-art methods, including the problems related to the translation of contact frequencies into Euclidean distances. Indeed, such a translation always produces a geometrically inconsistent distance set. Our multiscale chromatin model and our probabilistic solution approach allow us to partition the problem, thus speeding up the solution, to include suitable constraints, and to get multiple feasible structures. Moreover, the density function we use to sample the solution space does not require any translation from contact frequencies into distances.Source: Mathematical Models in Biology. Bringing Mathematics to Life, edited by Valeria Zazzu, Maria Brigida Ferraro, Mario R. Guarracino, pp. 161–171. Berlin Heidelberg: Springer, 2015
DOI: 10.1007/978-3-319-23497-7_12
Metrics:
See at:
ISTI Repository | doi.org 
| link.springer.com | CNR ExploRA
2016
Report
Open Access
Consistency tests for a recursive multi-scale 3D chromatin structure reconstruction algorithm
Caudai C., Salerno E., Zoppè M., Tonazzini A.
In this report, we test the consistency and coherence of an algorithm obtained as an extension of a technique we proposed in the past. This implements a recursive multi-scale reconstruction of the 3d chromatin structure from Chromosome Conformation Capture data. These data derive from millions of cells, so we cannot expect that they lead to a unique solution; for this reason, we adopt a statistic approach to sample the space of the solutions generated by a suitable objective function, in order to achieve congurations compatible with the input data and the known constraints. The consistency of the algorithm has been tested by producing a large number of results and evaluating the dispersion of the nal values of the objective function. Using the same solutions, synthetic contact matrices have been produced and compared with the input matrix to test the coherence of our solutions with the initial data. Furthermore, we investigated the presence of typical structures in the solutions by hierarchical clustering.Source: Project report, InterOmic, 2016
Caudai C., Salerno E., Zoppè M., Tonazzini A.
In this report, we test the consistency and coherence of an algorithm obtained as an extension of a technique we proposed in the past. This implements a recursive multi-scale reconstruction of the 3d chromatin structure from Chromosome Conformation Capture data. These data derive from millions of cells, so we cannot expect that they lead to a unique solution; for this reason, we adopt a statistic approach to sample the space of the solutions generated by a suitable objective function, in order to achieve congurations compatible with the input data and the known constraints. The consistency of the algorithm has been tested by producing a large number of results and evaluating the dispersion of the nal values of the objective function. Using the same solutions, synthetic contact matrices have been produced and compared with the input matrix to test the coherence of our solutions with the initial data. Furthermore, we investigated the presence of typical structures in the solutions by hierarchical clustering.Source: Project report, InterOmic, 2016
See at:
ISTI Repository | CNR ExploRA
2016
Other
Open Access
3D chromatin structure estimation through a constraint-enhanced score function
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Based on experimental techniques of the type "Chromosome Conformation Capture" (3C), several methods have been proposed in the literature to estimate the structure of the nuclear DNA in homogeneous populations of cells. Many of these methods transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid the drawbacks of this strategy, we propose to abandon the frequency-distance translation and adopt a recursive multiscale procedure, where the chromatin fibre is modelled by a new kind of modified bead chain, the data are suitably partitioned at each scale, and the resulting partial structures are estimated independently of each other and then connected again to rebuild the whole chain. We propose a new score function to generate the solution space: it includes a data-fit part that does not require target distances, and a penalty part, which enforces "soft" geometric constraints on the solution, coherent with known physical and biological constraints. The relative weights of the two parts are balanced automatically at each scale and each subchain treated. Since it is reasonable to expect that many different structures fit any 3C-type data set, we sample the solution space by simulated annealing, with no search for an absolute optimum. A set of different solutions with similar scores is thus generated. The procedure can be managed through a minimum set of parameters, independent of both the scale and the particular genomic segment being treated. The user is thus allowed to control the solutions easily and effectively. The partition of the fibre, along with several intrinsically parallel parts, make this method computationally efficient. We report some results obtained with the new method and code, tested against real data, that support the reliability of our method and the biological plausibility of our solutions.
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Based on experimental techniques of the type "Chromosome Conformation Capture" (3C), several methods have been proposed in the literature to estimate the structure of the nuclear DNA in homogeneous populations of cells. Many of these methods transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid the drawbacks of this strategy, we propose to abandon the frequency-distance translation and adopt a recursive multiscale procedure, where the chromatin fibre is modelled by a new kind of modified bead chain, the data are suitably partitioned at each scale, and the resulting partial structures are estimated independently of each other and then connected again to rebuild the whole chain. We propose a new score function to generate the solution space: it includes a data-fit part that does not require target distances, and a penalty part, which enforces "soft" geometric constraints on the solution, coherent with known physical and biological constraints. The relative weights of the two parts are balanced automatically at each scale and each subchain treated. Since it is reasonable to expect that many different structures fit any 3C-type data set, we sample the solution space by simulated annealing, with no search for an absolute optimum. A set of different solutions with similar scores is thus generated. The procedure can be managed through a minimum set of parameters, independent of both the scale and the particular genomic segment being treated. The user is thus allowed to control the solutions easily and effectively. The partition of the fibre, along with several intrinsically parallel parts, make this method computationally efficient. We report some results obtained with the new method and code, tested against real data, that support the reliability of our method and the biological plausibility of our solutions.
See at:
ISTI Repository | puma.isti.cnr.it | CNR ExploRA
2017
Journal article
Open Access
The SENSEable Pisa project: citizen-participation in monitoring acoustic climate of Mediterranean city centres
Vinci B., Tonacci A., Caudai C., De Rosa P., Nencini L., Pratali L.
The concept of urban sustainability and liveability closely depends on multi-level approaches to environmental issues. The ultimate goal in the field of noise management is to involve citizens and facilitate their participation in urban environmental decisions. The SENSEable Pisa project, based on the concept of Real-Time City and Smart City, presents an acoustic urban monitoring system based on a low-cost data acquisition method for a pervasive outdoor noise measurement. The system is based on the use of noise sensors located on private houses in the centre of Pisa, which provide a good model for the current acoustic climate of Mediterranean city centres. In this study, SENSEable acquisitions show a strong anthropogenic component not revealed by public strategic maps. The anthropogenic component, commonly known as movida, becomes increasingly critical in Mediterranean cities, therefore, it is necessary to explore methods highlighting this new source and to adopt strategies for the creation of reliable noise pollution maps.Source: Clean (Weinh., Internet) 45 (2017). doi:10.1002/clen.201600137
DOI: 10.1002/clen.201600137
Metrics:
Vinci B., Tonacci A., Caudai C., De Rosa P., Nencini L., Pratali L.
The concept of urban sustainability and liveability closely depends on multi-level approaches to environmental issues. The ultimate goal in the field of noise management is to involve citizens and facilitate their participation in urban environmental decisions. The SENSEable Pisa project, based on the concept of Real-Time City and Smart City, presents an acoustic urban monitoring system based on a low-cost data acquisition method for a pervasive outdoor noise measurement. The system is based on the use of noise sensors located on private houses in the centre of Pisa, which provide a good model for the current acoustic climate of Mediterranean city centres. In this study, SENSEable acquisitions show a strong anthropogenic component not revealed by public strategic maps. The anthropogenic component, commonly known as movida, becomes increasingly critical in Mediterranean cities, therefore, it is necessary to explore methods highlighting this new source and to adopt strategies for the creation of reliable noise pollution maps.Source: Clean (Weinh., Internet) 45 (2017). doi:10.1002/clen.201600137
DOI: 10.1002/clen.201600137
Metrics:
See at:
ISTI Repository | CLEAN - Soil Air Water | onlinelibrary.wiley.com | CNR ExploRA
2017
Contribution to conference
Open Access
3D Chromatin structure estimation from chromosome conformation capture data
Caudai C., Salerno E., Zoppè M., Tonazzini A.
In this communication we describe ChromStruct4, a method to reconstruct a set of plausible chromatin configurations starting from contact data obtained through Chromosome Conformation Capture techniques. Chromating fibre is modeled as a kinematic chain made of consecutive and partially penetrable beads whose properties (bead size, elasticity, curvature, etc.) can be suitably constrained. The chain can be divided in segments corresonding to Topological Association Domains. We do not search for a unique consensus configuration, because the experimental data are not derived from a single cell, but from millions of cells. We use a coarse-grained recoursive approach, based on a Simulated Annealing algorithm in order to sample the solution space. As opposed to most popular methods, we do not translate contact frequencies deterministically into distances, since this often produces structures that are not consistent with the Euclidean geometry, but adopt the assumption that loci with very high contact frequencies are actually close, but loci with low contact frequencies are not necessarily far away. ChromStruct4 is tested against real Hi-C data and compared with other methods for the 3-dimesional reconstruction fo Chromatin structure starting from Chromosome Conformation Capture data.Source: BITS 2017 - 14th Annual Meeting of the Bioinformatics Italian Society, Cagliari, Italy, 5-7 July 2017
Caudai C., Salerno E., Zoppè M., Tonazzini A.
In this communication we describe ChromStruct4, a method to reconstruct a set of plausible chromatin configurations starting from contact data obtained through Chromosome Conformation Capture techniques. Chromating fibre is modeled as a kinematic chain made of consecutive and partially penetrable beads whose properties (bead size, elasticity, curvature, etc.) can be suitably constrained. The chain can be divided in segments corresonding to Topological Association Domains. We do not search for a unique consensus configuration, because the experimental data are not derived from a single cell, but from millions of cells. We use a coarse-grained recoursive approach, based on a Simulated Annealing algorithm in order to sample the solution space. As opposed to most popular methods, we do not translate contact frequencies deterministically into distances, since this often produces structures that are not consistent with the Euclidean geometry, but adopt the assumption that loci with very high contact frequencies are actually close, but loci with low contact frequencies are not necessarily far away. ChromStruct4 is tested against real Hi-C data and compared with other methods for the 3-dimesional reconstruction fo Chromatin structure starting from Chromosome Conformation Capture data.Source: BITS 2017 - 14th Annual Meeting of the Bioinformatics Italian Society, Cagliari, Italy, 5-7 July 2017
See at:
ISTI Repository | CNR ExploRA
2017
Report
Open Access
Comparison between ChromStruct4 and TADbit
Caudai C., Salerno E., Zoppé M., Tonazzini A.
In this report performances of ChromStruct4 and tadbit have been compared. These are two methods for the inference of chromatin three-dimensional conformations starting from Chromosome Conforma- tion Capture data. tadbit and ChromStruct4 have been tested against the same data sets from real hi-c experiments. With comparative experi- ments, also robustness of ChromStruct4 against biases have been tested.Source: ISTI Technical reports, 2017
Caudai C., Salerno E., Zoppé M., Tonazzini A.
In this report performances of ChromStruct4 and tadbit have been compared. These are two methods for the inference of chromatin three-dimensional conformations starting from Chromosome Conforma- tion Capture data. tadbit and ChromStruct4 have been tested against the same data sets from real hi-c experiments. With comparative experi- ments, also robustness of ChromStruct4 against biases have been tested.Source: ISTI Technical reports, 2017
See at:
ISTI Repository | CNR ExploRA
2016
Report
Open Access
3D chromatin structure estimation through a constraint-enhanced score function
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Based on experimental techniques of the type Chromosome Conformation Capture (3c), several methods have been proposed in the literature to estimate the structure of the nuclear dna in homogeneous populations of cells. Many of these methods transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid the drawbacks of this strategy, we propose to abandon the frequency-distance translation and adopt a recursive multiscale procedure, where the chromatin fibre is modelled by a new kind of modified bead chain, the data are suitably partitioned at each scale, and the resulting partial structures are estimated independently of each other and then connected again to rebuild the whole chain. We propose a new score function to generate the solution space: it includes a data-fit part that does not require target distances, and a penalty part, which enforces soft geometric constraints on the solution, coherent with known physical and biological constraints. The relative weights of the two parts are balanced automatically at each scale and each subchain treated. Since it is reasonable to expect that many different structures fit any 3c-type data set, we sample the solution space by simulated annealing, with no search for an absolute optimum. A set of different solutions with similar scores is thus generated. The procedure can be managed through a minimum set of parameters, independent of both the scale and the particular genomic segment being treated. The user is thus allowed to control the solutions easily and effectively. The partition of the fibre, along with several intrinsically parallel parts, make this method computationally efficient. We report some results obtained with the new method and code, tested against real data, that support the reliability of our method and the biological plausibility of our solutions.Source: ISTI Working papers, 2016
DOI: 10.1101/075184
Metrics:
Caudai C., Salerno E., Zoppè M., Tonazzini A.
Based on experimental techniques of the type Chromosome Conformation Capture (3c), several methods have been proposed in the literature to estimate the structure of the nuclear dna in homogeneous populations of cells. Many of these methods transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid the drawbacks of this strategy, we propose to abandon the frequency-distance translation and adopt a recursive multiscale procedure, where the chromatin fibre is modelled by a new kind of modified bead chain, the data are suitably partitioned at each scale, and the resulting partial structures are estimated independently of each other and then connected again to rebuild the whole chain. We propose a new score function to generate the solution space: it includes a data-fit part that does not require target distances, and a penalty part, which enforces soft geometric constraints on the solution, coherent with known physical and biological constraints. The relative weights of the two parts are balanced automatically at each scale and each subchain treated. Since it is reasonable to expect that many different structures fit any 3c-type data set, we sample the solution space by simulated annealing, with no search for an absolute optimum. A set of different solutions with similar scores is thus generated. The procedure can be managed through a minimum set of parameters, independent of both the scale and the particular genomic segment being treated. The user is thus allowed to control the solutions easily and effectively. The partition of the fibre, along with several intrinsically parallel parts, make this method computationally efficient. We report some results obtained with the new method and code, tested against real data, that support the reliability of our method and the biological plausibility of our solutions.Source: ISTI Working papers, 2016
DOI: 10.1101/075184
Metrics:
See at:
bioRxiv | www.biorxiv.org | CNR ExploRA
2019
Journal article
Open Access
Estimation of the spatial chromatin structure based on a multiresolution bead-chain model
Caudai C., Salerno E., Zoppe M., Tonazzini A.
We present a method to infer 3D chromatin configurations from Chromosome Conformation Capture data. Quite a few methods have been proposed to estimate the structure of the nuclear DNA in homogeneous populations of cells from this kind of data. Many of them transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid inconsistencies, our method is based on a score function that does not require any frequency-to-distance translation. We propose a multiscale chromatin model where the chromatin fibre is suitably partitioned at each scale. The partial structures are estimated independently, and connected to rebuild the whole fibre. Our score function consists in a data-fit part and a penalty part, balanced automatically at each scale and each subchain. The penalty part enforces "soft" geometric constraints. As many different structures can fit the data, our sampling strategy produces a set of solutions with similar scores. The procedure contains a few parameters, independent of both the scale and the genomic segment treated. The partition of the fibre, along with intrinsically parallel parts, make this method computationally efficient. Results from human genome data support the biological plausibility of our solutions.Source: IEEE/ACM transactions on computational biology and bioinformatics (Print) 16 (2019): 550–559. doi:10.1109/TCBB.2018.2791439
DOI: 10.1109/tcbb.2018.2791439
Metrics:
Caudai C., Salerno E., Zoppe M., Tonazzini A.
We present a method to infer 3D chromatin configurations from Chromosome Conformation Capture data. Quite a few methods have been proposed to estimate the structure of the nuclear DNA in homogeneous populations of cells from this kind of data. Many of them transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid inconsistencies, our method is based on a score function that does not require any frequency-to-distance translation. We propose a multiscale chromatin model where the chromatin fibre is suitably partitioned at each scale. The partial structures are estimated independently, and connected to rebuild the whole fibre. Our score function consists in a data-fit part and a penalty part, balanced automatically at each scale and each subchain. The penalty part enforces "soft" geometric constraints. As many different structures can fit the data, our sampling strategy produces a set of solutions with similar scores. The procedure contains a few parameters, independent of both the scale and the genomic segment treated. The partition of the fibre, along with intrinsically parallel parts, make this method computationally efficient. Results from human genome data support the biological plausibility of our solutions.Source: IEEE/ACM transactions on computational biology and bioinformatics (Print) 16 (2019): 550–559. doi:10.1109/TCBB.2018.2791439
DOI: 10.1109/tcbb.2018.2791439
Metrics:
See at:
ISTI Repository | IEEE/ACM Transactions on Computational Biology and Bioinformatics | ieeexplore.ieee.org | CNR ExploRA
2020
Journal article
Open Access
A multifunctional alternative lawn where warm-season grass and cold-season flowers coexist
Bretzel F., Gaetani M., Vannucchi F., Caudai C., Grossi N., Magni S., Caturegli L., Volterrani M.
Lawns provide green infrastructure and ecosystem services for anthropized areas. They have a strong impact on the environment in terms of inputs (water and fertilizers) and maintenance. The use of warm-season grasses, such as Cynodon dactylon (L.) Pers., provides a cost-effective and sustainable lawn in the dry summers of the Mediterranean. In winter, Bermudagrass is dormant and brown, which instead of being a problem could be an opportunity for biodiversity through the coexistence of flowering species. This study assesses the possibility of growing autumn-to-spring-flowering bulbs and forbs with Bermudagrass, to provide ecosystem services in urban areas. Eight geophytes and 18 forbs were incorporated into a mature turf of hybrid Bermudagrass, Cynodon dactylon × C. transvaalensis cv. "Tifway". At the same time, a commercial flowering mix was sown in the same conditions. Two different soil preparations, scalping and turf flaming, and two different nitrogen doses, 50 and 150 kg ha, were carried out before sowing and transplanting. The flowering plants were counted. All the bulbs and six of the 18 forbs were able to grow and flower in the first and second years. The commercial mix was in full bloom from April until the cutting time for the hybrid Bermudagrass, at the end of May. Adding the flowering species did not affect the healthy growth of the warm-season grass. The fertilization dose had no effect, while turf flaming led to a wider spread of Bellis perennis L. and Crocus spp. Several flower-visiting insects were observed in the spring.Source: Landscape and ecological engineering (Print) 16 (2020): 307–317. doi:10.1007/s11355-020-00423-w
DOI: 10.1007/s11355-020-00423-w
Metrics:
Bretzel F., Gaetani M., Vannucchi F., Caudai C., Grossi N., Magni S., Caturegli L., Volterrani M.
Lawns provide green infrastructure and ecosystem services for anthropized areas. They have a strong impact on the environment in terms of inputs (water and fertilizers) and maintenance. The use of warm-season grasses, such as Cynodon dactylon (L.) Pers., provides a cost-effective and sustainable lawn in the dry summers of the Mediterranean. In winter, Bermudagrass is dormant and brown, which instead of being a problem could be an opportunity for biodiversity through the coexistence of flowering species. This study assesses the possibility of growing autumn-to-spring-flowering bulbs and forbs with Bermudagrass, to provide ecosystem services in urban areas. Eight geophytes and 18 forbs were incorporated into a mature turf of hybrid Bermudagrass, Cynodon dactylon × C. transvaalensis cv. "Tifway". At the same time, a commercial flowering mix was sown in the same conditions. Two different soil preparations, scalping and turf flaming, and two different nitrogen doses, 50 and 150 kg ha, were carried out before sowing and transplanting. The flowering plants were counted. All the bulbs and six of the 18 forbs were able to grow and flower in the first and second years. The commercial mix was in full bloom from April until the cutting time for the hybrid Bermudagrass, at the end of May. Adding the flowering species did not affect the healthy growth of the warm-season grass. The fertilization dose had no effect, while turf flaming led to a wider spread of Bellis perennis L. and Crocus spp. Several flower-visiting insects were observed in the spring.Source: Landscape and ecological engineering (Print) 16 (2020): 307–317. doi:10.1007/s11355-020-00423-w
DOI: 10.1007/s11355-020-00423-w
Metrics:
See at:
ISTI Repository | Landscape and Ecological Engineering | link.springer.com | CNR ExploRA