sourceforge.net - Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages...
https://pgapx.ybzhao.com/ - PGAP-X is a microbial comparative genomic analysis platform with graphic interface. Serials of algorithms and methodologies have been developed and integrated to analyze and visualize genomics structure variation, gene distribution with different...
github.com - bpRNA, a novel annotation tool capable of parsing RNA structures, including complex pseudoknot-containing RNAs, to yield an objective, precise, compact, unambiguous, easily-interpretable description of all loops, stems, and pseudoknots, along with...
pypi.org - The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also...
github.com - netGO is an R/Shiny package for network-integrated pathway enrichment analysis.netGO provides user-interactive visualization of enrichment analysis results and related networks.
Currently, netGO supports analysis for four species...
https://breedbase.org/ - Breedbase is a comprehensive breeding management and analysis software. It can be used to design field layouts, collect phenotypic information using tablets, support the collection of genotyping samples in a field, store large amounts of high...
www.bioinf.jku.at - The kebabs package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define...
https://r-graphics.org/ - R is powerful tool for data analysis, visualization, and machine learning. And it costs $0 to use! Here are six FREE books you can use to learn R...
github.com - find the resources we provide here useful in getting you set up to analyse and interpret your data.
To reference VESPA: https://peerj.com/preprints/1895/
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