Paper Info
Title
Measuring the State of the Art of Automated Pathway Curation Using Graph Algorithms - A Case Study of the mTOR Pathway.
Abstract
This paper evaluates the difference between human pathway curation and current NLP systems. We propose graph analysis methods for quantifying the gap between human curated pathway maps and the output of state-of-the-art automatic NLP systems. Evaluation is performed on the popular mTOR pathway. Based on analyzing where current systems perform well and where they fail, we identify possible avenues for progress.
Year
DOI
Venue
2016
10.18653/v1/W16-2916
BioNLP@ACL
DocType
Volume
ISSN
Conference
abs/1608.03767
Proceedings of the 15th Workshop on Biomedical Natural Language Processing, Berlin, Germany, 2016, pages 119-127. Association for Computational Linguistics
Citations 
PageRank 
References 
1
0.36
19
Authors
3
Name
Order
Citations
PageRank
Michael Spranger17813.70
Sucheendra K Palaniappan2343.93
Samik Ghosh321.05