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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 13

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Knowledge discovery using big data in biomedical systems

Divide and conquer approach to contact map overlap problem using 2D-pattern mining of protein contact networks

Biclustering with flexible plaid models to unravel interactions between biological processes

Unsupervised structure detection in biomedical data

Guest editorial for the 25th International Conference on Genome Informatics (GIW/ISCB-Asia 2014)

Randomized subspace learning for proline CIS-trans isomerization prediction

An O(m log m)-time algorithm for detecting superbubbles

An efficient search algorithm for finding genomic-range overlaps based on the maximum range length

Curatable named-entity recognition using semantic relations

Guest editors introduction to the special section on software and databases

ResSeq: enhancing short-read sequencing alignment by rescuing error-containing reads

MMBIRFinder: a tool to detect microhomology-mediated break-induced replication

Heterogeneous compression of large collections of evolutionary trees

ClusterViz: a cytoscape APP for cluster analysis of biological network

Building transcriptional association networks in cytoscape with RegNetC

iPFPi: a system for improving protein function prediction through cumulative iterations

Software suite for gene and protein annotation prediction and similarity search

Rapid assessment of adverse drug reactions by statistical solution of gene association network

Quantitative measurement of split of the second heart sound (S2)

An optimized LMMSE based method for 3D MRI denoising

RBioCloud: a light-weight framework for bioconductor and R-based jobs on the cloud

A new method for detecting protein complexes based on the three node cliques

Adaptive fuzzy consensus clustering framework for clustering analysis of cancer data

An integrated framework for functional annotation of protein structural domains

Bayesian normalization model for label-free quantitative analysis by LC-MS

Integrative data analysis of multi-platform cancer data with a multimodal deep learning approach

Optimal experimental design for gene regulatory networks in the presence of uncertainty

Statistical detection of intrinsically multivariate predictive genes

RPCA-based tumor classification using gene expression data

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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 1

Curatable named-entity recognition using semantic relations

Content Provider	ACM Digital Library
Author	Hsu, Yi-Yu Kao, Hung-Yu
Copyright Year	2015
Description	Author Affiliation: National Cheng Kung University, Tainan, Taiwan, R.O.C.(Kao, Hung-Yu; Hsu, Yi-Yu)
Abstract	Named-entity recognition (NER) plays an important role in the development of biomedical databases. However, the existing NER tools produce multifarious named-entities which may result in both curatable and non-curatable markers. To facilitate biocuration with a straightforward approach, classifying curatable named-entities is helpful with regard to accelerating the biocuration workflow. Co-occurrence Interaction Nexus with Named-entity Recognition (CoINNER) is a web-based tool that allows users to identify genes, chemicals, diseases, and action term mentions in the Comparative Toxicogenomic Database (CTD). To further discover interactions, CoINNER uses multiple advanced algorithms to recognize the mentions in the BioCreative IV CTD Track. CoINNER is developed based on a prototype system that annotated gene, chemical, and disease mentions in PubMed abstracts at BioCreative 2012 Track I (literature triage). We extended our previous system in developing CoINNER. The pre-tagging results of CoINNER were developed based on the state-of-the-art named entity recognition tools in BioCreative III. Next, a method based on conditional random fields (CRFs) is proposed to predict chemical and disease mentions in the articles. Finally, action term mentions were collected by latent Dirichlet allocation (LDA). At the BioCreative IV CTD Track, the best F-measures reached for gene/protein, chemical/drug and disease NER were 54 percent while CoINNER achieved a 61.5 percent F-measure. System URL: http://ikmbio.csie.ncku.edu.tw/coinner/introduction.htm.
Starting Page	785
Ending Page	792
Page Count	8
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2014.2366770
Volume Number	12
Issue Number	4
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-07-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Biomedical text mining Curated term identification Named-entity recognition
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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