dc.description.abstract | In this project, we have already developed several open softwares including BGSSJ,
GeneNetwork, ProteMiner-SSM, and ProtExt, for applications in transcriptomics and
proteomics research. Gene-expression profiling and proteomics studies are revolutionizing
biology. These high-throughput methodologies generate experimental data at rates that
exceed knowledge growth. A major challenge for researchers is to make biological sense
out of the large amounts of information proceeding from these experiments. The
interpretation of these experiments can be facilitated by well-presented functional
annotations, which provide an overview of the functions that predominate in clusters as
well as functional annotations for each gene. We have developed BGSSJ, an XML-based
Java application that organizes lists of interesting genes or proteins for biological
interpretation in the context of the Gene Ontology, which organizes information for
molecular function, biological processes and cellular components for a number of different
organisms. The application allows for easy and interactive querying using different gene
identifiers (GenBank ID, UniGene, SwissProt, gene symbol), generates a summary page
with listings of the frequencies of Gene Ontology annotations for each functional category
(cluster), and separate pages with listings of annotations for each gene in a cluster, and
provides quantitative and statistical output files. The visualization browser allows users to
navigate the cluster hierarchy displayed in a tree-like structure and explore the associated
genes or proteins of each cluster through a user-friendly interface. BGSSJ will save time
and enhance the ability to analyze gene expression and proteomics data. BGSSJ is
available at http://bgssj.sourceforge.net/.
Inferring genetic network architecture from time series data generated from
high-throughput experimental technologies, such as cDNA microarray, can help us to
understand the system behavior of living organisms. We (collaborated with Professor
Shui-Tein Chen’s lab) have developed an interactive tool, GeneNetwork, which provides
four reverse engineering models and three data interpolation approaches to infer
relationships between genes. GeneNetwork enables a user to readily reconstruct genetic
networks based on microarray data without having intimate knowledge of the
mathematical models. A simple graphical user interface enables rapid, intuitive mapping
and analysis of the reconstructed network allowing biologists to explore gene relationships
at the system level. Availability: Download from http://genenetwork.sbl.bc.sinica.edu.tw/.
The detailed information has been published in Bioinformatics 20, 2004, 3691–3693.
ProteMiner-SSM, co-developed with Prof. Yen-Jen Oyang’s lab, is a web server for
efficient analysis of similar protein tertiary substructures. Analysis of protein–ligand
interactions is a fundamental issue in drug design. As the detailed and accurate analysis of
protein–ligand interactions involves calculation of binding free energy based on
thermodynamics and even quantum mechanics, which is highly expensive in terms of
computing time, conformational and structural analysis of proteins and ligands has been
widely employed as a screening process in computer-aided drug design. The
ProteMiner-SSM web server is available at http://proteminer.csie.ntu.edu.tw/. The detailed
information has been published in Nucleic Acids Research, 2004, 32, W76-W82.
We have also developed a text-mining system for protein-protein interaction extraction,
called ProtExt. ProtExt can extract and report protein-protein interactions in the literature
abstracts available at the NCBI Entrez-PubMed system. Our approach is based on the link
grammar and we propose a novel template language (PETL) for extracting protein-protein
interactions embedded in sentences more accurately and customizably. With PETL,
biologists can easily add new templates when seeing a new type of link path. A prototype
web server based on ProtExt system has been implemented and is available at
http://protext.csie.org/. | en |