BOL

github.com - Long-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding...

lindenb.github.io - Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

amp.pharm.mssm.edu - With BioJupies you can produce in seconds a customized, reusable, and interactive report from your own raw or processed RNA-seq data through a simple user interface BioJupies now supports user accounts! Sign in from the top right corner of the page...

www.nabda.gov.ng - The Genetics, Genomics & Bioinformatics Department (GBBD) at NABDA is unique, encompassing all facets of modern genetics and bioinformatics research. Trans-disciplinary research being conducted in our laboratories would lead to cures for human...

github.com - What is PhyloHerb: PhyloHerb is a wrapper program to process genome skimming data collected from plant materials. The outcomes include the plastid genome (plastome) assemblies, mitochondrial genome assemblies, nuclear ribosomal DNAs...

RESPONSIBILITIES The candidate is expected to work on a variety of projects related to analysis of data from NGS, Mass Spectrometry, Flow Cytometry and other related modalities. The position expects hands-on work and a strong eye for detail. The...

kallisto Transcript abundance quantification from RNA-seq data (uses pseudoalignment for rapid determination of read compatibility with targets) Software (C++) https://pachterlab.github.io/kallisto/ Sailfish Estimation of isoform abundances...

RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as...

github.com - Scripts for the analysis of HGT in genome sequence data

homes.sice.indiana.edu - Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models...