github.com - GeneValidator helps in identifing problems with gene predictions and provide useful information extracted from analysing orthologs in BLAST databases. The results produced can be used by biocurators and researchers who need accurate gene...
www.e-rna.org - R-chie allows you to make arc diagrams of RNA secondary structures, allowing for easy comparison and overlap of two structures, rank and display basepairs in colour and to also visualize corresponding multiple sequence alignments and...
1000 Genomes data tutorial at ASHG
Structural variants presentation by
Jan Korbel
European Molecular Biology Laboratory (EMBL) Heidelberg Genome Biology Research...
github.com - Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are...
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...
Basics concepts of Probability: The Study of Randomness
Biostatistics is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine,...
web.mit.edu - We present methods for the automatic determination of genome correspondence. The algorithms enabled the automatic identification of orthologs for more than 90% of genes and intergenic regions across the four species despite the large number of...
www.broadinstitute.org - Spines is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation...
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...