Machine Learning in Biomedicine and Bioinformatics


The Seventh International Conference on Machine Learning and Applications (ICMLA’ 08)

December 11-13, 2008 – San Diego, CA, USA




Bioinformatics and Biomedicine continue to face challenges to deal with very large amounts of data. Mining biological data thus requires sophisticated machine learning techniques. The goal of the workshop is to promote development and applications of novel machine learning methods to solve problems in bioinformatics and biomedicine. Building upon the success of the workshop in 2007, we continue the workshop this year. The workshop will feature invited talks from noted experts in the field and the latest machine learning research in bioinformatics and biomedicine.  We welcome papers that describe novel machine learning problem formulations and novel machine learning algorithms. Topics includes, not limited to:

   Text mining and ontologies

   High-throughput storage/processing/analysis, e.g., gene expression data

   Visualization of large data sets

   Interpretation of experiments in the context of knowledge from databases

   Protein or gene interaction networks

   RNAi and microRNA analysis


   Mining sequences from massively parallel sequencing technology

   Genomic and proteomic sequence analysis

   Comparative genomics


   Epigenomics data analysis

   Systems biology


Paper submission due:                         June 15, 2008   July 15, 2008

Notification of acceptance:                  September 1, 2008

Camera-ready papers and Registration:   October 1, 2008

ICMLA Conference:                                        December 11-13, 2008


We invite papers on original research. All submitted papers will be peer reviewed and evaluated on originality, significance, technical soundness, and clarity of expression.


Papers for this workshop should be submitted by June 15, 2008   July 15, 2008, at the regular paper submission website ( Papers should not exceed a maximum of 6 pages (including abstract, body, tables, figures, and references) and should be submitted as a pdf in 2-column IEEE format. LaTeX document class files for 2-column format can be found on the IEEE Author Tools web page here.


All inquiries should be addressed to one of the co-chairs:

Dechang Chen: dchen [at]

Chris Ding: CHQDing [at]

Sun Kim: sunkim [at]


Program Committee:

Gurkan Bebek              Case Western Rserve University   USA

Chengpeng Bi               University of Missouri USA

Dechang Chen             Uniformed Services University of the Health Services USA

Justin Choi                    Indiana University USA

Chris Ding                   University of Texas at Arlington  USA

Jianwen Fang                University of Kansas USA

Jean Gao                        University of Texas at Arlington  USA

Tamer Kahveci              University of Florida   USA

Hyunsoo Kim                 Harvard University USA

Seungchan Kim              Arizona State University USA

Sun Kim                        Indiana University USA

Mark A. Kon                   Boston University USA

Dmitry Korkin                University of Missouri USA

Birong Liao                     Eli Lilly USA

Aiguo Li                          NCI/NIH USA

Jinze Liu                          University of Kentucky USA

Zhenqiu Liu                     University of Maryland Medicine USA

Yingshu Li                       Georgia State University USA

Feng Lou                          Clemson University USA

Chandan K. Reddy           Wyane State University USA

Li Sheng                            Drexel University USA

Konstantinos Sirlantzis     University of Kent UK

Aik Choon Tan                  Johns Hopkins University USA

Jiong Yang                         Case Western Rserve University   USA

Illhoi Yoo                         University of Missouri-Columbia USA

Xiaoyu Zhang                    California State University San Marcos USA