Computational Tools for Cheminformatics and Biomolecular Discovery

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Badapple

Bioactivity datamining associative promiscuity pattern learning engine. Badapple: promiscuity patterns from noisy evidence, Yang et al., J. Cheminfo. 8:29 (2016), DOI: 10.1186/s13321-016-0137-3. ChemAxon

Carlsbad

Bioactivity knowlegebase & hypotheses via chemical patterns. The CARLSBAD Database: A Confederated Database of Chemical Bioactivities, SL Mathias et al., Database, 2013, bat044, DOI: 10.1093/database/bat044. ChemAxon, Cytoscape

Convert

Convert mol formats ChemAxon

Depict

Depict molecules RDKit

Depict

Depict molecules Chemaxon

DGeom

Distance-geometry conformer generation RDKit, JSmol

DrugCentral

Drug knowledge integration database. DrugCentral 2018: an update , Ursu O, et al., Nucleic Acids Research, doi:10.1093/nar/gky963, 29 October 2018. Django, PostgreSql, ChemAxon

Exfiles

Expression profile analytics, with SABV (sex-as-biological-variable), with RNA-seq data from GTEx R, R-Shiny

JSME

JavaScript molecular editor, by P. Ertl & B. Bienfait peter.ertl.com

MolCloud

Molecule clouds (algorithm by P. Ertl & B. Rohde, Novartis) ChemAxon

Ro5

Lipinski Rule of 5 analysis ChemAxon, VCCLAB/eADMET

SmartsFilter

SMARTS filtering with built in Glaxo, Blake, and Oprea SMARTS sets ChemAxon

TIN-X

TIN-X: Target importance and novelty explorer Python, ES6, SASS, Linting, MySql, Solr, Docker, etc.

TIGA

TIGA: Target Illumination GWAS Analytics. From the NIH IDG Project, aggregated evidence from the NHGRI-EBI GWAS Catalog for gene-trait associations R, R-Shiny

Druglikeness

Druglikeness using DRUGS/ACD fragment analysis ChemAxon

repoDB

Drug repositioning database, developed by Adam Brown and Chirag Patel at Harvard, updated by Jeremy Yang at UNM with new versions of DrugCentral, AACT, and UMLS. R, R-Shiny
Sincere thanks to the software partners and providers whose cooperation and commitment to academic research allow these services to exist:

ChemAxon

CDK

Mesa

OpenEye

RDKit

ALLOWED USE: These applications are for limited, reasonable use by the scientific community and especially academic and non-profit researchers worldwide. Overuse will interfere with access and performance for others, so please be considerate. In general, all users should limit use to 5000 molecules per day. All usage is logged, and overuse may result in client IP blocking. For special requests such as high-volume jobs and collaboration inquiries contact the Translational Informatics Division. Input file sizes: Note that these web apps, given typical network throughput, are impractical for large input files. In most cases the app restricts input file sizes. In general files in excess of a few thousand lines (e.g. SMILES) should not be uploaded. For help contact Jeremy Yang.