Search Results for "transfer function model"

* GSA-SNP2 is a successor of GSA-SNP (Nam et al. 2010, NAR web server issue). GSA-SNP2 accepts human GWAS summary data (rs numbers, p-values) or gene-wise p-values and outputs pathway genesets ‘enriched’ with genes associated with the given phenotype. It also provides both local and global protein interaction networks in the associated pathways. * Article: SYoon, HCTNguyen, YJYoo, JKim, BBaik, SKim, JKim, SKim, DNam, "Efficient pathway enrichment and network analysis of GWAS summary data...

RELEASE NOTE: Get raxmlGUI 2.0 at the NEW PROJECT LOCATION: https://antonellilab.github.io/raxmlGUI/ raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used software for phylogenetic inference using maximum likelihood. A userfriendly graphical front-end for phylogenetic analyses using RAxML (Stamatakis, 2006). Please cite: Silvestro, Michalak (2012) - raxmlGUI: a graphical front-end for RAxML. Organisms Diversity and Evolution 12, 335-337. DOI:...

...By default, the class "GeneticCode" generates alternative genetic codes, with the reqirement of block structure, and, optionally, with the assumption of stereochemical or biosynthetic models (to impose the assumption of the adaptive model, simply filter the codes using the error_cost() function). See Appendix in Makukov & shCherbak (2017) for the description of the algorithm. The code requires Qt 5. To compile the provided example, run 'qmake' to produce the Makefile, and then run 'make' to compile the executable file. License: Public Domain.

This collection of tools forms the basis of a pipeline for the complete enumeration of the number of solutions present in a model that maximizes a single objective function.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic networks among microbial communities.