The Second International Symposium on Languages in Biology and Medicine (LBM) 2007

Authors: Su Jian and Christopher JO Baker

Normalizing biomedical terms by minimizing ambiguity and variability

One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of the terms. Soft string matching ...

Authors: Yoshimasa Tsuruoka, John McNaught and Sophia Ananiadou

Assessment of disease named entity recognition on a corpus of annotated sentences

In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other sema...

Authors: Antonio Jimeno, Ernesto Jimenez-Ruiz, Vivian Lee, Sylvain Gaudan, Rafael Berlanga and Dietrich Rebholz-Schuhmann

Exploiting and integrating rich features for biological literature classification

Efficient features play an important role in automated text classification, which definitely facilitates the access of large-scale data. In the bioscience field, biological structures and terminologies are des...

Authors: Hongning Wang, Minlie Huang, Shilin Ding and Xiaoyan Zhu

New challenges for text mining: mapping between text and manually curated pathways

Associating literature with pathways poses new challenges to the Text Mining (TM) community. There are three main challenges to this task: (1) the identification of the mapping position of a specific entity or...

Authors: Kanae Oda, Jin-Dong Kim, Tomoko Ohta, Daisuke Okanohara, Takuya Matsuzaki, Yuka Tateisi and Jun'ichi Tsujii

Comparative analysis of five protein-protein interaction corpora

Growing interest in the application of natural language processing methods to biomedical text has led to an increasing number of corpora and methods targeting protein-protein interaction (PPI) extraction. Howe...

Authors: Sampo Pyysalo, Antti Airola, Juho Heimonen, Jari Björne, Filip Ginter and Tapio Salakoski

Monitoring the evolutionary aspect of the Gene Ontology to enhance predictability and usability

Much effort is currently made to develop the Gene Ontology (GO). Due to the dynamic nature of information it addresses, GO undergoes constant updates whose results are released at regular intervals as separate...

Authors: Jong C Park, Tak-eun Kim and Jinah Park

Structuring an event ontology for disease outbreak detection

This paper describes the design of an event ontology being developed for application in the machine understanding of infectious disease-related events reported in natural language text. This event ontology is ...

Authors: Ai Kawazoe, Hutchatai Chanlekha, Mika Shigematsu and Nigel Collier

Gene Ontology density estimation and discourse analysis for automatic GeneRiF extraction

This paper describes and evaluates a sentence selection engine that extracts a GeneRiF (Gene Reference into Functions) as defined in ENTREZ-Gene based on a MEDLINE record. Inputs for this task include both a g...

Authors: Julien Gobeill, Imad Tbahriti, Frédéric Ehrler, Anaïs Mottaz, Anne-Lise Veuthey and Patrick Ruch

Automatic construction of rule-based ICD-9-CM coding systems

In this paper we focus on the problem of automatically constructing ICD-9-CM coding systems for radiology reports. ICD-9-CM codes are used for billing purposes by health institutes and are assigned to clinical...

Authors: Richárd Farkas and György Szarvas

Identification of transcription factor contexts in literature using machine learning approaches

Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While manual literature curation is expensive and l...

Authors: Hui Yang, Goran Nenadic and John A Keane