BOL

www.cbcb.umd.edu - Metagenomics sequencing projects collect samples of DNA from uncharacterized environments that may contain hundreds or even thousands of species. One of the main challenges in analyzing a metagenome is phylogenetic classification of raw sequence...

http://shinyheatmap.com/ - Background: Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in...

github.com - SGA is a de novo genome assembler based on the concept of string graphs. The major goal of SGA is to be very memory efficient, which is achieved by using a compressed representation of DNA sequence reads. More at https://github.com/jts/sga SGA...

evomics.org - The objective of this activity is to help you understand how to run Velvet in general, how to accurately estimate the insert size of a paired-end library through the use of Bowtie, the primary parameters of velvet, and the process...

www.topcoder.com - Learning greedy algo for biologist.  https://www.topcoder.com/community/data-science/data-science-tutorials/greedy-is-good/ This webpage is also useful for the...

The genome assemblers generally take a file of short sequence reads and a file of quality-value as the input. Since the quality-value file for the high throughput short reads is usually highly memory-intensive, only a few assemblers, best suited for...

Structural variation caller tools using long reads

We are a computational biology lab that develops novel methods for analysis of DNA and RNA sequences. Our research includes software for aligning and assembling RNA-seq data, whole-genome assembly, and microbiome analysis. We work closely with...

RGCB is organizing the 33rd Annual Convention of Indian Association for Cancer Research from 13th to 15th February 2014 with the theme "Discovery, Innovation and Translation in Cancer Research" Kindly log on to conference website...

Our research group is primarily focused on the analysis of whole genome sequence data to identify genetic variation (primarily structural variation) and examine their potential functional impact in disease phenotypes. We are particularly interested...