Journal of Computational Biology
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- CSA, Gale, Proquest, Mary Ann Liebert, Inc., and Liebert
A probabilistic model of neutral and selective dynamics of protein network evolution.
We describe a model-based approach for estimating the probability of network rewiring events during evolution. Our method builds on the standard duplication-and-divergence model and incorporates phylogenetic analysis to guide the comparison of protein networks across species. We apply our algorithm...
On contigs and coverage.
This work revisits the classic problem of coverage in genomic shotgun assembly (the "Lander-Waterman statistics"). A novel formulation, based on the analysis of an autonomous Markov automaton, is presented, and two main conclusions are derived. The first is an evaluation of the minimum multiplicity...
A genome-scale modeling approach to study inborn errors of liver metabolism: toward an in silico patient.
We propose an innovative computational workflow to model the alteration of metabolism caused by IEM and predict the metabolites and reactions that are affected by the mutation. Our workflow exploits a recent genome-scale metabolic network model of hepatocyte metabolism to identify metabolites accumu...
Alignment-free sequence comparison based on next-generation sequencing reads.
We study the power of genome comparison based on shotgun read data without assembly using three alignment-free sequence comparison statistics, D(2), D(*)(2) and D(s)(2), both theoretically and by simulations. Theoretical formulas for the power of detecting the relationship between two sequences rela...
Normal and compound poisson approximations for pattern occurrences in NGS reads.
We suggest using word patterns to analyze NGS data. Word pattern counting (the study of the probabilistic distribution of the number of occurrences of word patterns in one or multiple long sequences) has played an important role in molecular sequence analysis. However, no studies are available on th...
A generalized linear model for peak calling in ChIP-Seq data.
We introduce a new peak calling method based on the generalized linear model (GLMNB) that utilizes negative binomial distribution to model the tag count data and account for the variation of background tags that may randomly bind to the DNA sequence at varying levels due to local genomic structures...
SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.
We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell...
Dynamic modeling of miRNA-mediated feed-forward loops.
We propose a quantitative approach integrating an existing method for mixed FFL identification based on sequence analysis with differential equation modeling approach that permits us to select active FFLs based on their dynamics. Different models are assessed based on their ability to properly repro...
An S-System Parameter Estimation Method (SPEM) for biological networks.
We focus our attention on the latter area, and in particular, on parameterizing a dynamic network of oriented interactions between genes. By basing the parameterizing approach on a known power-law relationship model between connected genes (S-system), we are able to account for non-linearity in the...
A new genomic evolutionary model for rearrangements, duplications, and losses that applies across eukaryotes and prokaryotes.
We propose a new evolutionary model that integrates gene duplications and losses with genome rearrangements and that leads to genomes with either one (or a very few) circular chromosome or a collection of linear chromosomes. Our model is based on existing rearrangement models and inherits their line...