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Geospatial data is becoming increasingly important in many fields, including urban planning, environmental science, public health, and more. These tools can help you work with data from a variety of sources, including satellite imagery, GPS data,...

github.com - NGenomeSyn: an easy-to-use and flexible tool for publication-ready visualization of syntenic relationships across multiple genomes  NGenomeSyn [multiple (N) Genome Synteny], for publication-ready visualization of syntenic relationships of...

github.com - JBrowse is a fast, embeddable genome browser built completely with JavaScript and HTML5, with optional run-once data formatting tools written in Perl. Headline Features: Fast, smooth scrolling and zooming. Explore your genome with unparalleled...

www.csie.ntu.edu.tw - LIBSVM is an integrated software for support vector classification, (C-SVC, nu-SVC), regression (epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It supports multi-class classification. Since version 2.8, it...

chmille4.github.io - Scribl is a javascript, Canvas-based graphics library that easily generates biological visuals of genomic regions, alignments, and assembly data. Scribl can also be used in conventional offline pipelines, since everything needed to generate charts...

PhD opportunity at Université de Liège - Belgium The Bioinformatics and Systems Biology Unit of Université de Liège (Belgium) is looking for a highly motivated master student with programming skills for a PhD thesis project (4 years, fully...

The 10th North East Bioinformatics Network (NEBINet) Annual Coordinators' Meet organised by the Bioinformatics Centre, St Edmund's College, Shillong and sponsored by the Department of Biotechnology, Government of India, was held at St Edmund's...

This is to announce the second official conference of the Nigerian Bioinformatics and Genomics Network (NBGN). October 11-13,2021 at Landmark University, Omu-Aran, Kwara State and Zoom ( conference link to be announced...

github.com - It is designed to work with patterned data. Famous examples of problems related to patterned data are: recovering signals in networks after a stimulation (cascade network reverse engineering), analysing periodic signals.

Useful resources to therapy, disease, drug and drug-target network data