Search results for "Modeling and Simulation"

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

2020

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe “DeepWAS”, a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to…

A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model.

2018

International audience; In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clust…

Mathematical model of T-cell lymphoblastic lymphoma: disease, treatment, cure or relapse of a virtual cohort of patients

2017

International audience; T lymphoblastic lymphoma (T-LBL) is a rare type of lymphoma with a good prognosis with a remission rate of 85%. Patients can be completely cured or can relapse during or after a 2-year treatment. Relapses usually occur early after the remission of the acute phase. The median time of relapse is equal to 1 year, after the occurrence of complete remission (range 0.2–5.9 years) (Uyttebroeck et al., 2008). It can be assumed that patients may be treated longer than necessary with undue toxicity. The aim of our model was to investigate whether the duration of the maintenance therapy could be reduced without increasing the risk of relapses and to determine the minimum treatm…

A Thermodynamic Model of Monovalent Cation Homeostasis in the Yeast Saccharomyces cerevisiae

2016

Cationic and heavy metal toxicity is involved in a substantial number of diseases in mammals and crop plants. Therefore, the understanding of tightly regulated transporter activities, as well as conceiving the interplay of regulatory mechanisms, is of substantial interest. A generalized thermodynamic description is developed for the complex interplay of the plasma membrane ion transporters, membrane potential and the consumption of energy for maintaining and restoring specific intracellular cation concentrations. This concept is applied to the homeostasis of cation concentrations in the yeast cells of S. cerevisiae. The thermodynamic approach allows to model passive ion fluxes driven by the…

The role of spatial structure in the evolution of viral innate immunity evasion: A diffusion-reaction cellular automaton model

2020

Most viruses have evolved strategies for preventing interferon (IFN) secretion and evading innate immunity. Recent work has shown that viral shutdown of IFN secretion can be viewed as a social trait, since the ability of a given virus to evade IFN-mediated immunity depends on the phenotype of neighbor viruses. Following this idea, we investigate the role of spatial structure in the evolution of innate immunity evasion. For this, we model IFN signaling and viral spread using a spatially explicit approximation that combines a diffusion-reaction model and cellular automaton. Our results indicate that the benefits of preventing IFN secretion for a virus are strongly determined by spatial struct…

2018

Mobile genetic elements such as conjugative plasmids are responsible for antibiotic resistance phenotypes in many bacterial pathogens. The ability to conjugate, the presence of antibiotics, and ecological interactions all have a notable role in the persistence of plasmids in bacterial populations. Here, we set out to investigate the contribution of these factors when the conjugation network was disturbed by a plasmid-dependent bacteriophage. Phage alone effectively caused the population to lose plasmids, thus rendering them susceptible to antibiotics. Leakiness of the antibiotic resistance mechanism allowing Black Queen evolution (i.e. a "race to the bottom") was a more significant factor t…

FastaHerder2: Four Ways to Research Protein Function and Evolution with Clustering and Clustered Databases.

2016

The accelerated growth of protein databases offers great possibilities for the study of protein function using sequence similarity and conservation. However, the huge number of sequences deposited in these databases requires new ways of analyzing and organizing the data. It is necessary to group the many very similar sequences, creating clusters with automated derived annotations useful to understand their function, evolution, and level of experimental evidence. We developed an algorithm called FastaHerder2, which can cluster any protein database, putting together very similar protein sequences based on near-full-length similarity and/or high threshold of sequence identity. We compressed 50…

NESSie.jl – Efficient and intuitive finite element and boundary element methods for nonlocal protein electrostatics in the Julia language

2018

Abstract The development of scientific software can be generally characterized by an initial phase of rapid prototyping and the subsequent transition to computationally efficient production code. Unfortunately, most programming languages are not well-suited for both tasks at the same time, commonly resulting in a considerable extension of the development time. The cross-platform and open-source Julia language aims at closing the gap between prototype and production code by providing a usability comparable to Python or MATLAB alongside high-performance capabilities known from C and C++ in a single programming language. In this paper, we present efficient protein electrostatics computations a…

Health and Disease Imprinted in the Time Variability of the Human Microbiome

2017

The human microbiota correlates closely with the health status of its host. This article analyzes the microbial composition of several subjects under different conditions over time spans that ranged from days to months. Using the Langevin equation as the basis of our mathematical framework to evaluate microbial temporal stability, we proved that stable microbiotas can be distinguished from unstable microbiotas. This initial step will help us to determine how temporal microbiota stability is related to a subject’s health status and to develop a more comprehensive framework that will provide greater insight into this complex system.

SNVSniffer: an integrated caller for germline and somatic single-nucleotide and indel mutations

2016

Various approaches to calling single-nucleotide variants (SNVs) or insertion-or-deletion (indel) mutations have been developed based on next-generation sequencing (NGS). However, most of them are dedicated to a particular type of mutation, e.g. germline SNVs in normal cells, somatic SNVs in cancer/tumor cells, or indels only. In the literature, efficient and integrated callers for both germline and somatic SNVs/indels have not yet been extensively investigated. We present SNVSniffer, an efficient and integrated caller identifying both germline and somatic SNVs/indels from NGS data. In this algorithm, we propose the use of Bayesian probabilistic models to identify SNVs and investigate a mult…