BOL

pasapipeline.github.io - PASA, acronym for Program to Assemble Spliced Alignments, is a eukaryotic genome annotation tool that exploits spliced alignments of expressed transcript sequences to automatically model gene structures, and to maintain gene structure annotation...

http://readiab.org/ - IAB is primarily being developed by Greg Caporaso(GitHub/Twitter: @gregcaporaso) in the Caporaso Lab at Northern Arizona University. You can find information on the courses I teach on my teaching website and...

github.com - The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc...

bioinformatics.sdstate.edu - 2/3/2020: Now published by Bioinformatics. 11/3/2019: V 0.61, Improve graphical visualization (thanks to reviewers). Interactive networks and much more. 5/20/2019: V.0.60, Annotation database updated to Ensembl 96. New bacterial and fungal...

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...

advaitabio.com - The confusion about gene ontology and gene ontology analysis can start right from the term itself. There are actually two different entities that are commonly referred to as gene ontology or “GO”: the ontology itself, which is a...

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...

diytranscriptomics.com - A semester-long course covering best practices for the analysis of high-throughput sequencing data from gene expression (RNA-seq) studies, with a primary focus on empowering students to be independent in the use of lightweight and open-source...

A major breakthrough (replaced microarrays) in the late 00’s and has been widely used since Measures the average expression level for each gene across a large population of input cells Useful for comparative transcriptomics,...

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...