Room Location: Room B3

Presenter: Lars Juhl Jensen, EMBL, Germany, jensen@embl.de
Lars Jensen is an Associate Professor in the Comparative Sequence Analysis group of Prof. Peer Bork at the European Molecular Biology Laboratory, Heidelberg (EMBL), Germany. His research work focuses on literature mining and on integration of literature and large-scale experimental data. He has recently published a review on biological literature mining, in Nature Reviews Genetics. Besides lectures at undergraduate and graduate courses in Bioinformatics at the Technical University of Denmark (DTU), Dr. Jensen has given oral presentations at numerous conferences, meetings, and workshops. Currently, he is giving tutorial-like lectures on biological literature mining, for industry partners as well as DTU undergraduate students.

Contact: Click to send email

Abstract: To most biologists, hands-on literature mining is currently limited to using PubMed. However, methods for extracting facts from the biomedical literature have improved considerably, and the associated tools will likely soon be used in many laboratories to interpret large-scale experimental data sets and thereby to make biological discoveries.

Top

Room Location: Room B1

Presenter: Peter Schattner, University of California, Santa Cruz, USA, schattner@cse.ucsc.edu
Peter Schattner is a computational biologist at the University of California, Santa Cruz where his principal research interests are in computer-based methods for the detection and characterization of non-protein-coding RNAs. He has also been a developer for the Bioperl group for whom he has designed numerous software modules and contributed the project's tutorial documentation. In
addition to teaching regular university bioinformatics courses, Dr. Schattner has developed a tutorial presentation on Bioperl that was extremely well received at several conferences as well as three other recent tutorial reviews on the biology and computational aspects of non-coding RNAs. A recent review article was published in Trends in Genetics (PubMed link).

Contact: Click to send email

Abstract: The UCSC, Ensembl and NCBI genome databases integrate data from multiple, disparate sources in a uniform manner. However, developing automated queries to access these integrated databases has a considerable learning curve. Using realistic examples, participants will learn to design queries and programs enabling such automated analyses of genomic data.

Top

Room Location: Room B5

Presenter: Sebastián Bassi, Universidad Nacional de Quilmes, Argentina, sbassi@gmail.com
Sebastián Bassi is one of the developers of BioPython (http://www.biopython.org/participants/) and had contributed with web interface to EMBOSS programs using BioPython. He uses Python extensively in his work at Advanta Seeds, a plant biotech center in Balcarce, Argentina. He is also the main developer of DNALinux. Bassi has given several Linux and computer technology related courses. Recent tutorials include a DNALinux presentation in CAFECONF 2005 (Capital Federal Linux User Group Conference) at UADE (www.uade.edu.ar, www.cafeconf.org ) in Buenos Aires, Argentina and an Introduction to Linux for molecular biologists, at the Instituto de Investigaciones Biologicas, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Mar del Plata.

Contact: Click to send email

Abstract: Python is an object-oriented programming language that is very easy to use. Despite its user friendly nature, its very powerful and are available several modules that extends language capabilities, like BioPython. This tutorial will introduce how to use Python for everyday research uses, like data manipulation, XML processing, and cgi-interface.

Top

Room Location: Room B2

Presenter: Pierre Baldi, University of California, Irvine, USA, pfbaldi@ics.uci.edu
Pierre Baldi is Professor and Director of Institute for Genomics and Bioinformatics, at the University of California, Irvine. Dr. Baldi has over 20 years of experience in teaching and research in bioinformatics and chemoinformatics. He has published over 150 scientific articles and four books, including “Bioinformatics: the Machine Learning Approach” [MIT Press, Second Edition]. Besides giving tutorials at ISMB, NIPS, IJCNN and other major international conferences, he has recently given invited talks on chemoinformatics at IJCNN (International Joint Conference on Neural Networks, Montreal, Canada, August 2005) and GIW (International Conference on Genome Informatics, Yokohama, Japan, December 2005). He teaches bioinformatics and statistical machine learning classes at UCI and is currently developing a chemoinformatics curriculum.

Contact: Click to send email

Abstract: This self-contained tutorial will provide an overview of chemoinformatics, from foundations to state-of-the-art results and challenges. It will cover molecular and reaction data, data structures and the available algorithms for efficiently searching large repositories and annotating or predicting the physical, chemical, and biological properties of compounds and reactions with applications ranging from chemical genomics to drug discovery. The tutorial will leverage analogies and create synergies between bio and chemical informatics.

Additional Tutorial Authors: Sanjay J. Swamidass and J. Chen, University of California, Irvine, USA

Top

Room Location: Room E1

Presenters: Yanay Ofran, Columbia University, USA, ofran@maple.bioc.columbia.edu
Yanay Ofran is a post-doctoral scientist at the Columbia University Bioinformatics Center, working on protein-protein interfaces and DNA-Protein interactions. He is also interested in predicting protein function and the analysis of biological networks. Dr. Ofran has developed and taught several undergraduate and graduate level courses, including introductory courses in Bioinformatics (for undergraduates), and Biomedical Informatics and Computational Biology (for graduate students). Together with Dr. Marco Punta and Prof. Burkhard Rost, he has presented tutorials at ISMB2004 (judged “Best Quality tutorial”) as well as the Pacific Symposia of Biocomputing (PSB) in 2005 and 2006.

Marco Punta, Columbia University, New York, USA, mp2215@columbia.edu
A post-doctoral scientist at the Columbia University Bioinformatics Center, Marco Punta works on target selection and function annotation for structural genomics projects and prediction of protein contact maps. Dr. Punta has contributed to courses in Computational Biology at Columbia University and Genome Technology and Bioinformatics at the Marine Biological Lab., Massachusetts, USA. Recent presentations include tutorials at ISMB2004 and PSB2005.

Contact: Click to send email

Abstract: Currently, there are millions of sequences with little or no functional annotation. (1600 of them even have known 3D structure). In this tutorial we discuss the approaches and survey the tools available for studying function in silico, elaborating on open challenges. We use real-life examples from the literature to illustrate the strengths and weaknesses of current function prediction methods.

Additional Tutorial Author: Prof. Burkhard Rost, Columbia University, New York, USA

Top

Room Location: Room E2

Presenter: Olga Troyanskaya, Princeton University, ogt@princeton.edu
Olga Troyanskaya is an Assistant Professor in the Department of Computer Science and Lewis-Sigler Institute for Integrative Genomics at Princeton University. Her laboratory researches data integration, gene function prediction, and biological pathway modeling based on heterogeneous data. She was invited to author a review on data integration for Briefings in Bioinformatics. In addition to multiple seminar and workshop presentations, Dr. Troyanskaya developed and taught two bioinformatics courses at Princeton: Analysis and Visualization of Large-Scale Biological Data and Computational Modeling of Biological Networks. She teaches microarray analysis for the bioinformatics course at CSHL and taught bioinformatics at CalState Hayward.

Contact: Click to send email

Abstract: In the recent years, multiple types of high-throughput functional genomic data have become available that facilitate rapid functional annotation and pathway modeling in the sequenced genomes. Gene expression microarrays are the most commonly available source of such data, and increasing amount of other data, including protein-protein interactions, sequence, literature, and localization data are being generated. However, genomic data sacrifice specificity for scale compared to traditional experimental methods, yielding large quantities of relatively lower quality measurements.

Top

Room Location: Room B6

Presenters: Kirk Jordan, IBM, USA, kjordan@us.ibm.com
Kirk Jordan is the Emerging Solutions Executive in IBM's Deep Computing organization within the Systems and Technology Group. Dr. Jordan is a computational applied mathematician. He is active on US scientific committees on science and high-perfomance computing issues and has received several awards for his work on supercomputers. His main research interests lie in the efficient use of advanced architectures computers for simulation and modeling especially in the area of systems biology. He has authored numerous papers on performance analysis of advanced computer architectures and investigated methods that exploit these architectures. In 2005, he has presented tutorials at ISMB, the Sanibel Symposium and the APAC05, Gold Coast, Australia.

Srinivas Aluru, Iowa State University, USA, aluru@iastate.edu
Srinivas Aluru is a Professor of Electrical and Computer Engineering at the Iowa State University, Ames, USA. Prof. Aluru is the recipient of teaching awards including the IEEE Distinguished Visiting Speaker (2004-2006). His research interests include parallel models, algorithms and applications, computational biology and scientific computing. He has served as Tutorial Chair for the 12th IEEE International Conference on High Performance Computing, Goa, India, December 2005.

Scott Emrich, Iowa State University, USA, semrich@iastate.edu
Scott Emrich is a researcher in the Computational Biology and Scientific Computing Group at Iowa State University led by Dr. Srinivas Aluru. He is a computational biologist whose research interests include genome assembly, comparing multiple genomes and other large-scale problems in computational genomics. He has authored or co-authored multiple research papers and one book chapter on clustering and assembly of biological sequence data in parallel with an emphasis on maize genome assembly and analysis

Contact: Click to send email

Abstract: The complexity of biological systems demand both advanced computer architectures and innovative approaches to exploit them. We give an overview of the IBM Blue Gene system with a few biological examples of break through results. Through a detailed description of the Maize Genome Assembly, we show how to exploit this system.

Other Tutorial Authors: Charles DeLisi, Gyan Bhanot and Barbara Butler

Top

Room Location: Room E1

Presenters: Chris Needham, University of Leeds, UK, chrisn@comp.leeds.ac.uk
Chris Needham is a researcher at the School of Computing, University of Leeds, UK, working on protein function prediction using uncertainty, which involves predicting gene ontology classifications of proteins by integrating information from multiple sources. Dr. Needham has taught undergraduate courses on statistics, image and signal processing, computer vision, and a post-graduate course in perceptual sensory systems. His “introduction to Bayesian networks” talk was well received at the Leeds Annual Statistics Workshop, 2005. Together with Dr. Bradford, Dr. Bulpitt and Dr.Westhead, he has authored a primer on ‘Inference in Bayesian networks’ published recently in Nature Biotechnology (2006).

James Bradford, University of Leeds, UK, j.r.bradford@leeds.ac.uk
James Bradford is a research associate in the Leeds Bioinformatics research group. His main research interest is the prediction of protein function and protein-protein binding sites using machine learning methods such as support vector machines and Bayesian networks. Dr. Bradford’s teaching experience includes bioinformatics courses for post-graduate and undergraduate students.

Contact: Click to send email

Abstract: Bayesian networks provide a neat compact representation for expressing joint probability distributions and for inference. They are becoming increasingly important in biology for inferring cellular networks and pathways, biological data integration and genetics. This tutorial introduces the Bayesian approach to inference and learning parameters and structures for Bayesian networks.

Other Tutorial Authors: Dr. Andrew Bulpitt and Dr. David Westhead, University of Leeds, UK.

Top

Room Location: Room E2

Presenters: Baltazar Aguda, Mathematical Biosciences Institute, USA, bdaguda@mbi.osu.edu
Dr. Aguda is presently affiliated with the Mathematical Biosciences Institute at Ohio State University, USA where he is writing a graduate textbook on mathematical models of cell-fate regulation. He is interested in pathways databases relevant to regulatory networks of the cell cycle, apoptosis, and associated intracellular signaling. Dr. Aguda has 15 years of teaching experience in Canadian and US universities and has given tutorials at the Summer Course on Modeling Biological Systems, Humboldt University, Berlin, Germany (2003) and at the annual American Physical Society Meeting, Montreal, Canada (2004).

Andrew Goryachev, Centre for Integrative Systems Biology, University of Edinburgh, Edinburgh, UK, andrew_goryachev@yahoo.com
Andrew Goryachev is a RCUK Fellow at the Centre for Integrative Systems Biology, University of Edinburgh. Dr. Goryachev’s main research focus is on the emergence of cooperative self-organized behavior in the complex networks of interacting molecules and cells. He current work is on the regulatory networks that control cycling of small GTPases and he is developing methods for the representation, database storage and analysis of the cell interaction networks in the immune system. Concurrently, he is actively involved in graduate teaching in bioengineering and systems biology.

Contact: Click to send email

Abstract: This tutorial will first provide a primer on online pathway resources and ontologies. The focus will then shift to the topics of extracting network models from pathways databases,
modeling at different levels of resolution, the methods and tools of network analysis and
simulation, and on the qualitative analysis of networks with incomplete or uncertain
information. Lastly, a specific biological network involved in the mammalian cell cycle
will be used to illustrate the methods discussed

Top

Room Location: Room B5

Presenter: Jacques Colinge, Upper Austria University of Applied Sciences at Hagenberg, Austria, Jacques.colinge@fh-hageneberg.at
Jacques Colinge is a Professor of Bioinformatics at the UAS at Hagenberg, Austria, following several years of industry experience. He currently teaches mathematics, computer programming, introduction to bioinformatics algorithms, computational proteomics and statistical methods in bioinformatics. His research interests include proteomics data analysis (identification, quantitation and characterization), statistical methods, integration of proteomics and systems biology and parallel computing. He has recently presented a tutorial on Computational Proteomics at the European Conference in Computational Biology (ECCB05), Madrid, Spain.

Contact: Click to send email

Abstract: Proteomics has become an important approach to analyze biological samples. This tutorial will introduce the central problem of searching mass spectrometry data against a database. Quantitative proteomics and peptide de novo sequencing will be covered as well. This presentation should stimulate the interest of bioinformatics researchers in other fields and provide a concise introduction to life scientists.

Top

Room Location: Room B1

Presenters: Uwe Ohler, Duke University, USA, uwe.ohler@duke.edu
Uwe Ohler is an Assistant Professor in Computational Biology at Duke University’s Institute for Genome Sciences and Policy. He has extensive research experience in experience in pattern recognition and machine learning, sequence analysis, comparative genomics, evolution and computational-biological modelling. Dr. Ohler lectures in computer science and computational biology courses for undergraduate and graduate students. Since 2005, he has served as a member of the curriculum and student advisory committees of the Duke Graduate Program in Computational Biology and Bioinformatics.

Dirk Holste, University of Vienna, Austria, holste@alum.mit.edu
Dirk Holste is a Group Leader in genomics and computational molecular biology with research interests in genome and transcriptome quantitative analysis, comparative genomics, evolution and mathematical-biological modelling. Besides teaching graduate and undergraduate courses, Dr. Holste supervises research projects in computational biology of RNA sequence analysis and comparative genomics.

Contact: Click to send email

Abstract: To control gene expression under diverse contexts, it is exerted as a complex network at the level of both transcription and post-transcription. We propose an integrated tutorial on the biology of and current computational approaches for post-transcriptional gene regulation, with a focus on (alternative) splicing of mRNAs, an essential step of RNA processing in metazoans.

Top

Top

Room Location: Room B2

Presenters: Anna Panchenko, National Center for Biotechnology Information, USA, panch@ncbi.nlm.nih.gov
Anna R Panchenko, Ph.D., is a staff scientist at the National Center for Biotechnology Information, NIH. Her research interests include protein-protein interactions, protein domain classification, protein structure evolution and prediction of protein structure and functional sites. She is one of the organizers of the DIMACS-2006 workshop on protein function prediction. Dr Panchenko is an adjunct faculty member at George Washington University and Johns Hopkins University; she teaches the courses "Introduction to Bioinformatics" and "Computational aspects of molecular structure".

Benjamin Shoemaker, National Center for Biotechnology Information, USA, shoemake@mail.nih.gov
Benjamin Shoemaker, Ph.D., is a staff scientist at the National Center for Biotechnology Information, NIH, USA, working on protein-protein interactions, the development of databases for functional annotation and protein domain classification, and methods for protein interaction prediction. He has created a database of protein domain interactions which is based on the analysis of structurally conserved patterns. He also helped to develop the NCBI Conserved Domain Database.

Contact: Click to send email

Abstract: This tutorial will survey available databases and computational resources for studying protein interactions and discuss the theory behind various approaches of organizing the interactions. The challenge is to find novel and relevant interactions from large experimental sets. The focus will be on network analysis, verification and prediction of protein interactions.

Top