Tutorials

  1. Tutorials Tutorials of InCoB 2008 will be held on Thursday October 23, 2008. Conference participants interested in attending these tutorials are requested to sign up when they register for the conference by checking the appropriate boxes in the application form. Tutorials include:
    1. BioSlax and BioSlax Server: A Complete Freeware Open Source Solution for your Practical Bioinformatics Course
      Tutorial Presenters: Tan Tin Wee, Justin Choo, Jean Lim and Mark De Silva, Singapore
      Tutorial Programme
    2. Asian Variome Project (AVP).
      Tutorial Presenter: Jong Bhak, KOBIC, Korea.
    3. Information Visualization for High Dimensional Biomedical Data:the Matrix Visualization Approach
      Tutorial Presenter: Chun-Houh Chen, Academia Sinica, Taiwan Han-Ming Wu, Tamkang University, Taiwan
    4. The Proteomic Code and Related Technologies
      Tutorial Presenter: Jan Biro, Homulus Foundation, Sweden.
      WITHDRAWN
    5. Biological Networks: Insight from Interactions
      Tutorial Presenter: Prashanth Suravajhala, Roskilde University, Greater Copenhagen
  2. Post-InCoB Workshop on Education in Bioinformatics and Computational Biology Workshop Website http://trg.apbionet.org/webcb/ In addition to the tutorials, the IUBMB-FAOBMB-APBioNet Workshop on Education in Bioinformatics and Computational Biology (WEBCB) will be organised in conjunction with the 20th FAOBMB Taipei Conference (http://www.tsbmb.org.tw/FAOBMB/program.html) in the afternoon (1400h - 1700h). This workshop is kindly sponsored by IUBMB and the APBioNet.

    This Workshop organizing committee is co-chaired by Angela Jean, Jean Lim and Justin Choo. WEBCB Education Advisor: Shoba Ranganathan

  3. FAOBMB Education Program This workshop is free to all registered participants of InCoB and FAOBMB Conference Topic: Bioinformatics and systems approaches for disease study Presenter: Prof. Ueng-Cheng Yang (National Yang-Ming University, Taiwan)

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Tutorial 1: BioSlax and BioSlax Server: A Complete Freeware Open Source Solution for your Practical Bioinformatics Course
Justin Choo, Jean Lim and Mark De Silva, Singapore
 
Many teachers and trainers of bioinformatics and computational biology face a recurrent problem of keeping their software tools and databases up to date. In addition, they have to set up entire clusters of PCs installed with up-to-date software applications which they intend to teach. This is very troublesome and as a consequence takes up a lot of time and effort, and distracts from the teaching/learning process. Our solution is to package a whole list of commonly used software into a single LiveCD/DVD that includes an entire operating system (Slax). This system called BioSlax has been in use for several years at the National University of Singapore. A server version and a VMWare version are also available. With the BioSlax Server version, one can set up an entire server with a terabyte harddisk to act as a classroom bioinformatics server within minutes which can work in conjunction with the BioSlax LiveCDs. This tutorial will cover the basics of getting up to speed with using BioSlax and the BioSlax Server. TOP

Tutorial 2: Asian Variome Project
Jong Bhak, KOBIC, KRIBB, Korea
 
Aim of the workshop To advertise the AVP for bioinformatics researchers in Asia. AVP requires bioinformatics experts to analyze SNP and mutation data in collaboration. Program:

  1. Introduction of AVP
  2. Networking with other projects HVP(Human Variome Project): ttp://www.humanvariomeproject.org/ PASNP(Pan Asia SNP): http://pasnp.org eIMBL(electronic International Molecular Biology Lab.): http://www.eimbl.org/ KOVAC(Koran Variome Consortium)
  3. Bioinformatics for large scale SNP, mutation, and phenotype data

Duration: 3 hours Planned Speakers: Bioinformatics researchers and SNP researchers. Expected results: Provide a platform for launching AVP in Asia TOP


Tutorial 3: Information Visualization for High Dimensional Biomedical Data: the Matrix Visualization Approach
Professor Chun-Houh Chen, Academia Sinica, Taiwan Dr. Han-Ming Wu, Tamkang University, Taiwan
 
Exploratory data analysis (EDA, Tukey, 1977) has been introduced and extensively used for more than 30 years yet boxplot and scatterplot are still the major EDA tools for visualizing continuous data in the 21st century. On the other hand, multiple morrespondence analysis (MCA) type of methods (HOMALS: Gifi, 1990; MCA: Benzecri et al., 1973; Dual Scaling: Nishisato, 1984) and mosaic plots (Hartigan and Kleiner,1981; Friendly, 1994) are most popular in practice for visualizing multivariate categorical data. But all these methods loose their efficiency when data dimensionality gets really high (hunderds/thousands), particularly when data is of nominal nature. Matrix visualization (MV, Chen, 2002; Tien et al., 2008; Wu et al., 2008) on the other hand can simultaneously explore the associations of up to thousands of variables, subjects, and their interactions, without reducing dimension. MV permutes rows and columns of the raw data matrix together with two corresponding proximity matrices by suitable seriation (reordering) algorithms. These permuted matrices are then displayed as matrix maps through suitable color spectra for extracting the subject-clusters, variable-groups, and the subjects/variables interaction patterns. For binary, ordinal, and nominal data types, conventional visualization techniques (boxplot, scatterplot (matrix), mosaic display, parallel coordinate plot, etc.) basically cannot provide users much visual information while the categorical generalized association plots (cGAP), by integrating matrix visualization and dual scaling techniques, can effectively present complex patterns for thousands of categorical variables for thousands of subjects in one matrix visualization. When every sample point is affiliated to one region (polygon) in a physical or conceptual map, Cartography GAP extends the power of cGAP in summaryzing information structure of high-dimensional categorical data in a single map with various linking functions to cGAP in displaying more comprehensive information patterns. We believe GAP related matrix visualization techniques have great potential to become major data/information visualization tools for next generation EDA. In this lecture I will first briefly introduce the technical background of MV for continuous, binary, and nominal data types using the Generalized Association Plots (GAP) developed by our laboratory of information visualization. Real applications to scientific problems from biomedical experiments, psychometric studies, and social surveys will then be presented followed by ongoing developments and potential future directions for MV research. Related information and software (currently for continuous and binary data only; we hope to release the cGAP package soon) can be obtained from http://gap.stat.sinica.edu.tw/Software/index.htm. Potential participants are encouraged to download the Java version of GAP with user manual before attending the training course. TOP

WITHDRAWN 10 Oct 2008Tutorial 4: The Proteomic Code and Related Technologies
Jan Biro, Homulus Foundation, Sweden
 
Background The Proteomic Code is a set of rules by which information in genetic material is transferred into the physico-chemical properties of amino acids. It determines how individual amino acids interact with each other during folding and in specific protein-protein interactions. The Proteomic Code is part of the redundant Genetic Code. Review The 25-year-old history of this concept is reviewed from the first independent suggestions by Biro and Mekler, through the works of Blalock, Root-Bernstein, Siemion, Miller and others, followed by the discovery of a Common Periodic Table of Codons and Nucleic Acids in 2003 and culminating in the recent conceptualization of partial complementary coding of interacting amino acids as well as the theory of the nucleic acid-assisted protein folding. Methods and conclusions A novel cloning method for the design and production of specific, high-affinity-reacting proteins (SHARP) is presented. This method is based on the concept of proteomic codes and is suitable for large-scale, industrial production of specifically interacting peptides. Impact on the field / relevance A cutting edge biotechnology is based on the original theory of Proteomic Code and Nucleic Acid Assisted Protein Folding. The inventor, Biro (as scientist) has officially been declared to be in US National Interest (since 2006). Tutorial outline

  1. Computational and theoretical background of the Proteomic Code
  2. Computational and theoretical background of the Nucleic Acid Assisted Protein Folding (nucleic acid chaperons).
  3. Design and Production of Specifically interacting oligopeptides.
  4. Recent results
  5. Consultation

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Tutorial 5: Biological Networks: Insight from Interactions
Prashanth Suravajhala, Roskilde University, Greater Copenhagen
 
Post genomic era has ushered to say ’Ome’ for integrated biology disciplines. The complete sequencing of the human genome has shown us a new era of Systems Biology (SB) referred to as omics’. From genomics to proteomics and furthermore, ‘Omics’-es existing nowadays integrate many areas of biology. This resulted in an essential ascent from Bioinformatics to Systems Biology leaving room for identifying number of interactions in a cell. Tools have been developed to utilize evolutionary relationships towards understanding uncharacterized proteins while there is a need to generate and understand functional interaction networks. A systematic understanding of genes and proteins in a regulatory network has resulted in bringing the birth of System Biology (SB), there by raising several questions unanswered. Through this tutorial, we will dig some questions on why and how interactions especially protein-protein interactions (PPI) are useful while discussing methods to remove false positives by validating the data. TOP

FAOBMB workshop: Bioinformatics and systems approaches for disease study
Prof. Ueng-Cheng Yang, National Yang Ming University, Taiwan
 
Hypothesis-driven research is an effective approach to discover biological knowledge. Observation and hypothesis testing are usually based on the wet laboratory experiments. In the post-genomic era, high throughput techniques have produced mass amount of bioinformation. Therefore, it is possible to use in silico approach to discover the components related to a phenomenon and trace the biological pathways. For example, the knock-down (KD) or knock-out (KO) experiment may observe the relation of one gene to a few genes. The in silico approach will take advantage of the microarray data collected from a system perturbed by a series of internal or external factors. This novel approach may provide convincing evidence that is equivalent to KD or KO experiment. Moreover, a gene regulatory network can be constructed from such a genome-wide approach. Integrating gene network with protein interaction network will further suggest the possible mechanism for biological regulation. These hypotheses can then be tested by experimental approaches. The first part of this workshop will explain the rationale behind in silico approach and compare this novel approach with wet laboratory approach. The second part will explain the bioinformatics and statistical tools that are used in the in silico approach. The application of these tools on the disease problem will mainly focus on predicting the disease candidate gene, identify the disease subtype-specific pathways, and the possible regulation mechanisms. TOP