K. E. Ravikumar

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In this paper we describe a new named entity extraction system. Our system is based on a manually developed set of rules that rely heavily upon some crucial lexical information, linguistic constraints of English, and contextual information. This system achieves state of art results in the protein name detection task, which is what many of the current name(More)
MOTIVATION A large volume of experimental data on protein phosphorylation is buried in the fast-growing PubMed literature. While of great value, such information is limited in databases owing to the laborious process of literature-based curation. Computational literature mining holds promise to facilitate database curation. RESULTS A rule-based system,(More)
We participated in the BioNLP Shared Task 2011, addressing the GENIA event extraction (GE) and the Epigenetics and Post-translational Modifications (EPI) tasks. A graph-based approach is employed to automatically learn rules for detecting biological events in the life-science literature. The event rules are learned by identifying the key contextual(More)
The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison of(More)
MOTIVATION Phosphorylation is an important biochemical reaction that plays a critical role in signal transduction pathways and cell-cycle processes. A text mining system to extract the phosphorylation relation from the literature is reported. The focus of this paper is on the new methods developed and implemented to connect and merge pieces of information(More)
BACKGROUND Temporal information detection systems have been developed by the Mayo Clinic for the 2012 i2b2 Natural Language Processing Challenge. OBJECTIVE To construct automated systems for EVENT/TIMEX3 extraction and temporal link (TLINK) identification from clinical text. MATERIALS AND METHODS The i2b2 organizers provided 190 annotated discharge(More)
A web-based version of the RLIMS-P literature mining system was developed for online mining of protein phosphorylation information from MEDLINE abstracts. The online tool presents extracted phosphorylation objects (phosphorylated proteins, phosphorylation sites and protein kinases) in summary tables and full reports with evidence-tagged abstracts. The tool(More)
BACKGROUND We propose a method for automatic extraction of protein-specific residue mentions from the biomedical literature. The method searches text for mentions of amino acids at specific sequence positions and attempts to correctly associate each mention with a protein also named in the text. The methods presented in this work will enable improved(More)
The creation of biological pathway knowledge bases is largely driven by manual effort to curate based on evidences from the scientific literature. It is highly challenging for the curators to keep up with the literature. Text mining applications have been developed in the last decade to assist human curators to speed up the curation pace where majority of(More)
We propose a method enabling automatic extraction of protein-specific residues from the biomedical literature. We aim to associate mentions of specific amino acids to the protein of which the residue forms a part. The methods presented in this work will enable improved protein functional site extraction from articles, ultimately supporting protein function(More)