Text mining biomedical

Zweigenbaum, P., Demner-Fushman, D., Yu, H., Cohen, K.B. 2007. Frontiers of biomedical text mining current progress. Briefings in Bioinformatics. 8(5) 358-375. 

A compendium of Free, Public, Biomedical Text Mining Tools, Project Arrowsmith. University of Illinois at Chicago. URL http //arrowsmith.psych.uic.edu/arrowsmith uic/tools.html. 

There are a variety of text sources for biomedical text mining (see table 6.1). Abstract collections are the text sources, or corpora, that are easiest to access. One can also collect full-text patent collections from the various resellers or from the Patent Authorities directly (U.S. Patent Office, European Patent Office, World Intellectual Property Office, etc.). Other sources include full-text journal articles, Web documents, and news articles. 

Document Corpora Sources for Biomedical Text Mining... 

Do not use the early biomedical text-mining systems which give co-occurrence as output, as mere co-occurrence of two terms cannot be indicative of a definitive relationship between aity two entities, say a gene and a disease. 

Briefly discuss the visuahzation programs used for biomedical text-mining results. 

Rodriguez-Esteban R (2009) Biomedical text mining and its applications. PLoS Comput Biol 5(12) el000597... 

Lourenco A, Carreira R, Carneiro S, Maia P, Glez-Pena D, Fdez-Riverola F, Ferreira EC, Rocha I, Rocha M (2009) Note a workbench for biomedical text mining. J Biomed Inf 42 710-720... 

Papanikolaou N, Pafilis E, Nikolaou S, Ouzounis CA, Iliopoulos I, Promponas VJ (2011) BioTextQuest a web-based biomedical text mining suite for concept discovery. Bioinformatics 27 3327-3328... 

Tanabe L et al. MedMiner an internet text-mining tool for biomedical information, with application to gene expression profiling. BioTechniques 1999 27 1210-1217. 

The concept-based identification of biomedical entities is now being offered by most commercial vendors of text mining solutions and by an increasing number of academic tools.31 Biomedical concept search is mainly based on publicly available thesauri such as MeSH or GO (see below). 

At this point, there are many different biomedical literature publishers and various resellers of literature content that provide access to their published literature. Few recognize the importance of text mining to increasing the value of their literature holdings. Therefore, it may be quite difficult to negotiate full-text literature access. Because Open Access journals have only recently become available, their scope is limited and cannot be relied on exclusively. 

Entity extraction is the process of tagging things in the text as specific items such as genes, cell lines, people, chemical compounds, and so on. Two specific requirements for entity extraction are unique and critical to biomedical applications of text mining. Gene name disambiguation and chemical compound name tagging require different approaches. 

Leroy, G., Chen, H., Martinez J. D. et al. 2003. Genescene Biomedical text and data mining. Information retrieval and data mining. fCDL 03 Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries. 116-118. 

In the following section, we will explore a practical way to text mining biomedical hterature from MEDLINE. For demonstration, we used LingPipe, a free tool available for downloading from the Internet. In order to use LingPipe effectively, the interested readers are encouraged to visit the website and download the jar file or zip file containing all the detailed instractions. Here, we will de-... 

When it comes to processing millions of biomedical-related documents, one computer may not be sufficient. This is where distributed platforms for text mining can be applied. Distributed text mining is text mining in a distributed computing... 

J-ProLINE (Java-based Protein-ligand Network) is an interactive tool that detects relationships between hgand, scaffolds, protein sequence and stractures which are finally validated through biomedical literature-based text mining [39]. Its func-... 

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