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http://compbio.cs.princeton.edu/conservation/
Software for scoring protein sequence conservation using the Jensen-Shannon divergence. It can be used to predict catalytic sites and residues near bound ligands.
Proper citation: Conservation (RRID:SCR_016064) Copy
Software tool for genome and metagenome distance estimation using MinHash. Reduces large sequences and sequence sets to small, representative sketches, from which global mutation distances can be rapidly estimated.
Proper citation: Mash (RRID:SCR_019135) Copy
http://www.tsl.ac.uk/groups/bioinformatics/
Core develops tools for high throughput sequence data to study non reference, non model organisms.
Proper citation: Sainsbury Laboratory Bioinformatics Core Facility (RRID:SCR_017185) Copy
https://sdrc.stanford.edu/sdrc-research-cores/dgac/home/
Core facility that offers library preparation and sequencing services on a variety of platforms - Illumina HiSeq 4000, MiSeq, HiSeq 2500 and PacBio Sequel - as well as bioinformatics analysis. It can sequence a variety of commercial sample preparation kits as well as custom workflows. DGAC provides access to high throughput sequencing and analysis to researchers at the Stanford Diabetes Research Center.
Proper citation: Stanford Diabetes Research Center Diabetes Genomics Analysis Core (RRID:SCR_016213) Copy
http://hihg.med.miami.edu/software-download/seqem-version-1.0
Online tool for utilizing a genotype calling algorithm for next-generation sequence data.
Proper citation: SeqEM (RRID:SCR_002021) Copy
http://code.google.com/p/rnao/
An ontology to capture all aspects of RNA - from primary sequence to alignments, secondary and tertiary structure from base pairing and base stacking to sophisticated motifs.
Proper citation: RNA Ontology (RRID:SCR_003470) Copy
http://purl.obolibrary.org/obo/flu/
An application ontology established by a collaborative group of influenza researchers that includes consolidated influenza sequence and surveillance terms from resources such as the BioHealthBase (BHB), a Bioinformatics Resource Center (BRC) for Biodefense and Emerging and Re-emerging Infectious Diseases, the Centers for Excellence in Influenza Research and Surveillance (CEIRS)
Proper citation: Influenza Ontology (RRID:SCR_003346) Copy
http://blocks.fhcrc.org/blocks/codehop.html
This COnsensus-DEgenerate Hybrid Oligonucleotide Primer (CODEHOP) strategy has been implemented as a computer program that is accessible over the World-Wide Web and is directly linked from the BlockMaker multiple sequence alignment site for hybrid primer prediction beginning with a set of related protein sequences. This is a new primer design strategy for PCR amplification of unknown targets that are related to multiply-aligned protein sequences. Each primer consists of a short 3' degenerate core region and a longer 5' consensus clamp region. Only 3-4 highly conserved amino acid residues are necessary for design of the core, which is stabilized by the clamp during annealing to template molecules. During later rounds of amplification, the non-degenerate clamp permits stable annealing to product molecules. The researchers demonstrate the practical utility of this hybrid primer method by detection of diverse reverse transcriptase-like genes in a human genome, and by detection of C5 DNA methyltransferase homologs in various plant DNAs. In each case, amplified products were sufficiently pure to be cloned without gel fractionation. Sponsors: This work was supported in part by a grant from the M. J. Murdock Charitable Trust and by a grant from NIH. S. P. is a Howard Hughes Medical Institute Fellow of the Life Sciences Research Foundation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.
Proper citation: COnsensus-DEgenerate Hybride Oligonucleotide Primers (RRID:SCR_002875) Copy
https://github.com/cobilab/altair
Software C toolkit for alignment free and spatial temporal analysis of multi-FASTA data. Used for entangling presence of multiple sequences from epidemic and pandemic events.
Proper citation: AltaiR (RRID:SCR_024752) Copy
https://github.com/liukai5016/FungiLT
Software classifier tool based on deep learning methods for classification and annotation of large-scale fungal ITS sequences. Used for fungal species classification.
Proper citation: FungiLT (RRID:SCR_025886) Copy
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