Biological Text Classification : BioCreAtIvE II Challenge sub - task 1
نویسندگان
چکیده
The BioCreAtIvE II PPI IAS is a biomedical text classification task which concerns whether a given abstract contains protein interaction information. In order to improve the performance of text classification, we examined ways to represent text from the term type and term weighting aspects. In addition, we also combined different classifiers by simple majority voting technique.
منابع مشابه
Identifying Protein-Protein interactions in Biomedical publications
The paper describes the approaches and the results of our participation in the protein-protein interaction (PPI) extraction task (sub-tasks 1 to 3) of the BioCreative II challenge. The core of our approach is to analyse the logical forms of those sentences which contain the mentioning of relevant protein names, and to rank the sentences from which the relations where extracted using the class d...
متن کاملExtracting Interacting Protein Pairs and Evidence Sentences by using Dependency Parsing and Machine Learning Techniques
The biomedical literature is growing rapidly. This increases the need for developing text mining techniques to automatically extract biologically important information such as protein-protein interactions from free texts. Besides identifying an interaction and the interacting pair of proteins, it is also important to extract from the full text the most relevant sentences describing that interac...
متن کاملTesting Extensive Use of NER tools in Article Classification and a Statistical Approach for Method Interaction Extrac- tion in the Protein-Protein Interaction Literature
We participated (as Team 81) in the Article Classification (ACT) and Interaction Method (IMT) subtasks of the Protein-Protein Interaction task of the Biocreative III Challenge. For the ACT we pursued an extensive testing of available Named Entity Recognition (NER) tools, and used the most promising ones to extend our the Variable Trigonometric Threshold (VTT) linear classifier we successfully u...
متن کاملThe Gene Ontology Task at BioCreative IV
Gene Ontology (GO) annotation is a common task among model organism database (MOD) groups. It is a very time-consuming and labor-intensive task, thus often considered as one of the bottlenecks in literature curation. There is a growing need for semior fully-automated GO curation techniques that will help database curators rapidly and accurately identify gene function information in full-length ...
متن کاملFeature generation and representations for protein-protein interaction classification
Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007