craven [at] biostat.wisc.edu
Professor, Department of Biostatistics & Medical Informatics and Department of Computer Science.
*Machine Learning and Gene Regulation
I am interested in developing and applying machine learning methods for uncovering the regulatory mechanisms of cells. This work involves automatically constructing predictive models for such tasks as (i) recognizing transcription control signals, (ii) assigning genes to operons, and (iii) identifying expression relationships among genes. This work involves sequence, gene-expression, functional annotation and textual data sources.
*Machine Learning and Information Extraction
I am interested in developing automated methods that enable text sources to be better exploited for discovery and decision making in biomedical domains. One main focus of this work is in developing automated methods for extracting structured representations (e.g. database tuples) from on-line biomedical text sources, such as MEDLINE. Our approach is to use machine learning methods to induce information-extraction routines from training examples.
For an up-to-date listing of publications, please see Mark Craven's webpage.
Introduction to Bioinformatics
Machine learning methods for uncovering the regulatory mechanisms of cells. Sequence, gene-expression, functional annotation and textual data sources.