RECCR Rensselaer Exploratory Center for Cheminformatics Research
News Members Projects Publications Software Data MLI ECCRS
Targeted Task Models for Cheminformatics Process Development

Multi-Task Modeling

Ion-exchange chromatography is inherently a multi-task problem. Each task involves predicting the retention times under different experimental conditions. Simultaneously modeling these tasks can improve insight into the causal model underlying the methods. PLS was developed for such multi-task and multi-response models but PLS is limited to least squares regression loss functions. Multiple Latent Analysis (MLA) extends BLF to multi-task problems optimized using any convex loss function (Xhang 2004). With MLA, we can modeling the tasks as interrelated ranking problems in order to determine which experimental conditions are likely to achieve the desired protein replacement order. Recently SVM’s have also been extend to multi-task modeling (Evegeniou and Pontil 2004). Thus we would like to investigate both multi-task SVM and MLA to cheminformatics applications. In chromatography, retention times for specific proteins may not be available for all of the proteins across all of the tasks. In the flexibility of the MLA and SVM approaches, we can alter the objective to exploit all available information to exploit all available data by allowing missing data. Ultimately we could tackle problems like what are the key proteins that should be tested to understand the characteristic a particular operating condition. Interpretation and visualization techniques could be used to investigate the common properties of these proteins. Note multi-task modeling is applicable to many problems in cheminformatics. For example in drug discovery, we typically want to model and optimize several properties of small molecules related to efficacy, absorption, and toxicity.

Previous || Next

Rensselaer Polytechnic Institute RECCR Home Page || Member Area || Wiki

Copyright ©2005 Rensselaer Polytechnic Institute
All rights reserved worldwide.