NDLI: Comparison of vector space model methodologies to reconcile cross-species neuroanatomical concepts

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Development of a model for microphysiological simulations : Small nodes of ranvier from peripheral nerves of mice reconstructed by electron tomography

A new era in computational neuroscience

Neuroinformatics : Volume 3, Issue 1, March 2005

Neuroinformatics : Volume 2

Neuroinformatics : Volume 1

Comparison of vector space model methodologies to reconcile cross-species neuroanatomical concepts

Content Provider	Springer Nature Link
Author	Srinivas, P. R. Wei, Shang Heng Cristianini, Nello Jones, E. G. Gorin, F. A.
Copyright Year	2005
Abstract	Generating informational thesauri that classify, cross-reference, and retrieve diverse and highly detailed neuroscientific information requires identifying related neuroanatomical terms and acronyms within and between species (Gorin et al., 2001) Manual construction of such informational thesauri is laborious, and we describe implementing and evaluating a neuroanatomical term and acronym reconciliation (NTAR) system to assist domain experts with this task. NTAR is composed of two modules. The neuroanatomical term extraction (NTE) module employs a hidden Markov model (HMM) in conjunction with lexical rules to extract neuroanatomical terms (NT) and acronyms (NA) from textual material. The output of the NTE is formatted into collections of term- or acronym-indexed documents composed of sentences and word phrases extracted from textual material. The second information retrieval (IR) module utilizes a vector space model (VSM) and includes a novel, automated relevance feedback algorithm. The IR module retrieves statistically related neuroanatomical terms and acronyms in response to queried neuroanatomical terms and acronyms. Neuroanatomical terms and acronyms retrieval obtained from term-based inquiries were compared with (1) term retrieval obtained by including automated relevance feedback and with (2) term retrieval using “document-to-document” comparisons (context-based VSM). The retrieval of synonymous and similar primate and macaque thalamic terms and acronyms in response to a query list of human thalamic terminology by these three IR approaches was compared against a previously published, manually constructed concordance table of homologous cross-species terms and acronyms. Term-based VSM with automated relevance feedback retrieved 70% and 80% of these primate and macaque terms and acronyms, respectively, listed in the concordance table. Automated feedback algorithm correctly identified 87% of the macaque terms and acronyms that were independently selected by a domain expert as being appropriate for manual relevance feedback. Context-based VSM correctly retrieved 97% and 98% of the primate and macaque terms and acronyms listed in the term homology table. These results indicate that the NTAR system could assist neuroscientists with thesauri creation for closely related, highly detailed neuroanatomical domains.
Starting Page	115
Ending Page	131
Page Count	17
File Format	PDF
ISSN	15392791
Journal	Neuroinformatics
Volume Number	3
Issue Number	2
e-ISSN	15590089
Language	English
Publisher	Humana Press
Publisher Date	2005-01-01
Publisher Place	Totowa
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Neurosciences Computer Application in Life Sciences Neurology Biotechnology Computational Biology/Bioinformatics
Content Type	Text
Resource Type	Article
Subject	Neuroscience Information Systems Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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