https://link.springer.com/epdf/10.1186/s12864-018-5330-5?author_access_token=ICASEpyMAQaxLlKw--fyCG_BpE1tBhCbnbw3BuzI2RMA57KLmXk5bZabRUiDQzRFHXd6hjm4kWSiLV3mU5XVMitqXUwFMSo4x5vbfty0EDQ9PW1sd1h923_TYXkvJ5niSwAyZ7BklJ0ujFAFhcKtjw%3D%3D

Address of the bookmark: https://webs.iiitd.edu.in/raghava/humcfs/

More at https://software.broadinstitute.org/gatk/download/bundle

ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/.

ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/

Address of the bookmark: https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1

More recently, we've been enthused about using k-mer based similarity measures and computing and searching k-mer-based sketch search databases for all the things.

But I haven't spent too much talking about using k-mers for taxonomy, although that has become an ahem area of interest recently, if you read into our papers a bit.

In this blog post I'm going to fix this by doing a little bit of a literature review and waxing enthusiastic about other people's work. Then in a future blog post I'll talk about how we're building off of this work in fun! and interesting? ways!

Address of the bookmark: http://ivory.idyll.org/blog/2017-something-about-kmers.html

• dbCAN provides the capability of automated and comprehensive CAZyme annotation of a given genome submitted by the user;
• dbCAN provides an explicitly defined signature domain for each and every CAZyme family along with its location in all the relevant full-length CAZyme proteins in all sequenced genomes;
• dbCAN provides the most complete set of metagenomic CAZyme genes published so far and represents the first step towards discovering novel CAZyme catalysts in metagenomes;
• dbCAN provides a subfamily classification of the existing CAZyme families based on sequence similarities;
• dbCAN make all pre-computed data freely available to the public, including sequence alignments, hidden markov models (HMMs) and phylogenies of the signature domain regions in each and every CAZyme family and subfamily.

dbCAN is updated regularly when CAZy database created new families based on latest literature.

Address of the bookmark: http://csbl.bmb.uga.edu/dbCAN/index.php

Ref https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/

Address of the bookmark: https://github.com/likelet/LncPipe

If you have a license key for Modeller 8 or 9, there is no need to reregister for Modeller 9.13 - the same license key will work. (It won't do any harm to reregister if you want to, though!)

9.13 is primarily a bugfix release relative to the last public release(9.12). Major user-visible changes include:

# Modeller now includes a variety of SOAP (statistically optimized atomic potential) scores for assessing proteins, loops, and interfaces.

# The Lennard-Jones interaction energy is now artificially truncated at very short distance; this makes simulations with poor starting conditions much less likely to 'blow up'.

# model.get_insertions(), model.get_deletions() and model.loops() now have an include_termini option; if False, residue ranges that include chain termini are excluded from the output.

See the Modeller manual for a full change log: http://salilab.org/modeller/9.13/manual/node39.html

If you encounter bugs in Modeller 9.13, please see http://salilab.org/modeller/9.13/manual/node10.html for information on how to report them.

Reference:

http://salilab.org/modeller/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/datasets/coronavirus/genomes/

Address of the bookmark: http://www.softberry.com/berry.phtml?topic=fgenesh&group=help&subgroup=gfind

Address of the bookmark: https://www.ncbi.nlm.nih.gov/geo/geo2r/

More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html