BioTextQuest+ – Literature Mining and Concept Discovery

BioTextQuest+

:: DESCRIPTION

BioTextQuest (BTQ) implements an enhanced version of the TextQuest algorithm (proposed by Iliopoulos et al., 2001), providing a user friendly web-based interface. BTQ collects abstracts fromMedline literature and OMIM databases matching a user query. Identification of relevant terms enables the representation of text records in a Vector Space Model and the calculation of pairwise document similarities. Employing suitable clustering algorithms, results are transformed into clusters of records along with their corresponding terms. BTQ, besides the document processing and clustering algorithms, relies on public web services such as NCBI eSearchReflect, and WhatIzIt to query biomedical databases and to annotate and enrich the biomedically significant terms. Data Integration and further bioinformatics analysis related to the tagged bioentities is available through BioCompendium service. Additional added-value features include a variety of clustering, stemming, co-occurence analysis and visualization algorithms/techniques allowing interactive result navigation.

 

::DEVELOPER

Ioannis Iliopoulos’ Bioinformatics & Computational Biology Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BioTextQuest+: A knowledge integration platform for literature mining and concept discovery.
Papanikolaou N, Pavlopoulos GA, Pafilis E, Theodosiou T, Schneider R, Satagopam VP, Ouzounis CA, Eliopoulos AG, Promponas VJ, Iliopoulos I.
Bioinformatics. 2014 Aug 6. pii: btu524.

MPTM 1.0 – Mining Protein post-Translational Modifications from literature

MPTM 1.0

:: DESCRIPTION

MPTM is a web-based text mining tool that extracts and incorporates comprehensive knowledge about post-translational modification with their underlying substrate,enzyme,site,disease,and etc. This tool integrates available data not only from the published literature but also from the biological databases. Currently, users can browse the web server MPTM and see the results by entering the name of protein or other terms. Moreover, users can download data in the MPTMDB. In addition, using the “Interaction Search” to find potential substrate-enzyme associations.

::DEVELOPER

HI_Lab @ USTC

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Sun D, Wang M, Li A.
MPTM: A tool for mining protein post-translational modifications from literature.
J Bioinform Comput Biol. 2017 Oct;15(5):1740005. doi: 10.1142/S0219720017400054. Epub 2017 Sep 11. PMID: 28982288.

Literature mining of protein phosphorylation using dependency parse trees.
Wang M, Xia H, Sun D, Chen Z, Wang M, Li A.
Methods. 2014 Jun 1;67(3):386-93. doi: 10.1016/j.ymeth.2014.01.008.

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