MedMeSH Summarizer: Text Mining for Gene Clusters

Kankar, Pankaj; Adak, Sudeshna; Sarkar, Anasua; Murali, Kaushik; Sharma, Gaurav

doi:10.1137/1.9781611972726.32

Cited by 40 publications

(24 citation statements)

References 23 publications

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“…[30] MedMeSH summarizer summarizes a group of genes by filtering biomedical literature and assigning relevant keywords describing the functionality of the genes. This system constructed a P∗Q co-occurrence matrix where P denotes the genes in the cluster and Q reflects the MeSH terms that were extracted from the retrieved literature.…”

Section: Methodsmentioning

confidence: 99%

A MeSH-based text mining method for identifying novel prebiotics

Shan

Lu²,

Min³

et al. 2016

Medicine

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Section: Methodsmentioning

confidence: 99%

A MeSH-based text mining method for identifying novel prebiotics

Shan

Lu²,

Min³

et al. 2016

Medicine

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“…For example Masys et al, (2001); Kankar et al, (2002) used MeSH terms, the former also using EC numbers. The above-mentioned works shared some limitations that result from attributes of GO and are also common in other curated data sources.…”

Section: Using Go a Representative Curated Resourcementioning

confidence: 99%

GeneNarrator: Mining the Literaturome for Relations Among Genes

Ding¹,

Berleant²,

Xu³

et al. 2009

J Proteomics Bioinform

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The rapid development of microarray and other genomic technologies now enables biologists to monitor the expression of hundreds, even thousands of genes in a single experiment. Interpreting the biological meaning of the expression patterns still relies largely on biologist's domain knowledge, as well as on information collected from the literature and various public databases. Yet individual experts' domain knowledge is insufficient for large data sets, and collecting and analyzing this information manually from the literature and/or public databases is tedious and time-consuming. Computer-aided functional analysis tools are therefore highly desirable.We describe the architecture of GeneNarrator, a text mining system for functional analysis of microarray data. This system's primary purpose is to test the feasibility of a more general system architecture based on a two-stage clustering strategy that is explained in detail. Given a list of genes, GeneNarrator collects abstracts about them from PubMed, then clusters the abstracts into functional topics in a first clustering stage. In the second clustering stage, the genes are clustered into groups based on similarities in their distributions of occurrence across topics. This novel two-stage architecture, the primary contribution of this project, has benefits not easily provided by onestage clustering.

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“…There are also tools like MeSHMap (Srinivasan 2001) and MedMeSH Summarizer (Kankar et al 2002) that exploits MeSH ontology for document indexation and summarization, respectively.…”

Section: Introductionmentioning

confidence: 99%

PATIENT-BASED LITERATURE RETRIEVAL AND INTEGRATION - A Use Case for Diabetes and Arterial Hypertension

Jimenez-Castellanos¹,

Fernández²,

Pérez-Rey³

et al. 2011

Proceedings of the International Conference on Health Informatics

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Abstract:Specialized search engines such as PubMed, MedScape or Cochrane have increased dramatically the visibility of biomedical scientific results. These web-based tools allow physicians to access scientific papers instantly. However, this decisive improvement had not a proportional impact in clinical practice due to the lack of advanced search methods. Even queries highly specified for a concrete pathology frequently retrieve too many information, with publications related to patients treated by the physician beyond the scope of the results examined. In this work we present a new method to improve scientific article search using patient information. Two pathologies have been used within the project to retrieve relevant literature to patient data and to be integrated with other sources. Promising results suggest the suitability of the approach, highlighting publications dealing with patient features and facilitating literature search to physicians.

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MedMeSH Summarizer: Text Mining for Gene Clusters

Cited by 40 publications

References 23 publications

A MeSH-based text mining method for identifying novel prebiotics

A MeSH-based text mining method for identifying novel prebiotics

GeneNarrator: Mining the Literaturome for Relations Among Genes

PATIENT-BASED LITERATURE RETRIEVAL AND INTEGRATION - A Use Case for Diabetes and Arterial Hypertension

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