cikm 2015 论文列表Proceedings of the ACM Ninth International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO 2015, Melbourne, Australia, October 23, 2015. |
Prediction of Scaffold Proteins based on Protein Interaction and Domain Architectures.
Cell line specific method based on functional modules for drug sensitivity prediction.
What-if Analysis in Biomedical Networks based on Production Rule System.
Analyzing Subject-Method Network of Bioinformatics and Biology.
A Flexible Text Mining System for Entity and Relation Extraction in PubMed.
A Text Mining Approach for Identifying Herb-chemical Relationships from Biomedical Articles.
Analyzing the Landscape of Anti-Cancer Drug Research in Pancreatic Cancer.
Citizen Organization System for Advanced MEDical research (COSAMED).
Identification and Analysis of Medical Entity Co-occurrences in Twitter.
Toxicity Predictions using Compound Descriptions.
Evaluation of Disease-Associated Text-Mining Databases.
Identifying Potential Bioactive Compounds of Natural Products by Combining ADMET Prediction Methods.
Development of a Framework for Constructing a Virtual Physiological Human with the Integration of COntext Specific Directed Associations (CODA).
Building Text-mining Framework for Gene-Phenotype Relation Extraction using Deep Leaning.
Prognostic Factor Analysis for Breast Cancer Using Gene Expression Profiles.
Prediction of Compound-Target Interactions of Natural Products Using Large-scale Drug and Protein Information.
In-silico Interaction-Resolution Pathway Activity Quantification and Application to Identifying Cancer Subtypes.
Discovery of Prostate Specific Antigen Pattern to Predict Castration Resistant Prostate Cancer of Androgen Deprivation Therapy.
Evaluation of a Machine Learning Duplicate Detection Method for Bioinformatics Databases.
Extraction of Fine-grained Semantic Relations for the Human Variome.
Privacy Preserving Data Anonymization of Spontaneous ADE Reporting System Dataset.
The Effect of Word Sense Disambiguation Accuracy on Literature Based Discovery.