Machine Learning and Bioinformatics (MLB) Group
The MLB Group aims to design algorithms and to develop tools for analyzing large amounts of data, in particular, molecular sequence and gene expression data. Our main projects are focused on:
- Ontology engineering and classifier learning from semantically heterogeneous data sources
- Genomic sequence analysis, alternative splicing discovery and gene prediction
- Gene regulatory network discovery from gene expression data and sequence information
The MLB group is collaborating with the Artificial Intelligence and Machine Learning group at Iowa State University to produce an open-source system for knowledge acquisition and information integration from semantically heterogeneous data sources (NSF funding), and with the Bioinformatics Center at KSU to produce bioinformatics and genomics tools (funding from KSU EcoGen and KSU Targeted Excellence Program).
IR Class and Friends, Fall 2011
