Search results for "imulation"
showing 10 items of 7271 documents
Rev-Erb modulates retinal visual processing and behavioral responses to light
2016
International audience; The circadian clock is thought to adjust retinal sensitivity to ambient light levels, yet the involvement of specific clock genes is poorly understood. We explored the potential role of the nuclear receptor subfamily 1, group D, member 1 (REV-ERB; or NR1D1) in this respect. In light-evoked behavioral tests, compared with wild-type littermates, Rev-Erb(-/-) mice showed enhanced negative masking at low light levels (0.1 lx). Rev-Erb(-/-) mouse retinas displayed significantly higher numbers of intrinsically photosensitive retinal ganglion cells (ipRGCs; 62% more compared with wild-type) and more intense melanopsin immunostaining of individual ipRGCs. In agreement with a…
Neuronal Activity Patterns in the Developing Barrel Cortex
2017
International audience; The developing barrel cortex reveals a rich repertoire of neuronal activity patterns, which have been also found in other sensory neocortical areas and in other species including the somatosensory cortex of preterm human infants. The earliest stage is characterized by asyn-chronous, sparse single-cell firing at low frequencies. During the second stage neurons show correlated firing, which is initially mediated by electrical synapses and subsequently transforms into network bursts depending on chemical synapses. Activity patterns during this second stage are synchronous plateau assemblies, delta waves, spindle bursts and early gamma oscillations (EGOs). In newborn rod…
Assessment of in vivo organ-uptake and in silico prediction of CYP mediated metabolism of DA-Phen, a new dopaminergic agent
2017
Abstract The drug development process strives to predict metabolic fate of a drug candidate, together with its uptake in major organs, whether they act as target, deposit or metabolism sites, to the aim of establish a relationship between the pharmacodynamics and the pharmacokinetics and highlight the potential toxicity of the drug candidate. The present study was aimed at evaluating the in vivo uptake of 2-Amino-N-[2-(3,4-dihydroxy-phenyl)-ethyl]-3-phenyl-propionamide (DA-Phen) − a new dopaminergic neurotransmission modulator, in target and non-target organs of animal subjects and integrating these data with SMARTCyp results, an in silico method that predicts the sites of cytochrome P450-m…
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.
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.
2021
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2′-o-ribose methyltransferase). Supported by…
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…
parSRA: A framework for the parallel execution of short read aligners on compute clusters
2018
The growth of next generation sequencing datasets poses as a challenge to the alignment of reads to reference genomes in terms of both accuracy and speed. In this work we present parSRA, a parallel framework to accelerate the execution of existing short read aligners on distributed-memory systems. parSRA can be used to parallelize a variety of short read alignment tools installed in the system without any modification to their source code. We show that our framework provides good scalability on a compute cluster for accelerating the popular BWA-MEM and Bowtie2 aligners. On average, it is able to accelerate sequence alignments on 16 64-core nodes (in total, 1024 cores) with speedup of 10.48 …
Targeting Bacterial Sortase A with Covalent Inhibitors: 27 New Starting Points for Structure-Based Hit-to-Lead Optimization.
2019
Because of its essential role as a bacterial virulence factor, enzyme sortase A (SrtA) has become an attractive target for the development of new antivirulence drugs against Gram-positive infections. Here we describe 27 compounds identified as covalent inhibitors of
Assessing statistical significance in multivariable genome wide association analysis
2016
Motivation: Although Genome Wide Association Studies (GWAS) genotype a very large number of single nucleotide polymorphisms (SNPs), the data are often analyzed one SNP at a time. The low predictive power of single SNPs, coupled with the high significance threshold needed to correct for multiple testing, greatly decreases the power of GWAS. Results: We propose a procedure in which all the SNPs are analyzed in a multiple generalized linear model, and we show its use for extremely high-dimensional datasets. Our method yields P-values for assessing significance of single SNPs or groups of SNPs while controlling for all other SNPs and the family wise error rate (FWER). Thus, our method tests whe…
Stagewise pseudo-value regression for time-varying effects on the cumulative incidence
2015
In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event s…