2006~2008 Research Highlight
- Our research focuses on computer-aided drug discovery and structural bioinformatics. We have developed a molecular docking tool (namely GEMDOCK) which is one of wide-used docking tools in the world. We cooperated with 10 research teams on diverse drug targets and experimental results demonstrate that our tools are useful for discovering lead compounds (e.g. dengue virus envelop protein, skimate kinases, and influenza virus neuraminidase), identifying functional sites (e.g. ß-lactoglobulin), and protein engineering (e.g. endo-chitosanase to exo-chitosanase). We published 7 papers on top journals in these fields and these papers were cited over 70 times since 2004. We get the 2007 National Innovation Award due to the achievement of iGEMDOCK which is graphic interface of GEMODCK. The iGEMDOCK was downloaded over 1,200 times and was used for education.
- For structural bioinformatics, we have achieved successful results on protein structure prediction (PS2), fast protein structure search (3D-BLAST), and structural protein-protein interaction networks (3D-partner). These results were published on the top journals (such as Nucleic Acids Research and Genome Biology) in these fields. A particularly exciting success is the development of the 3D-BLAST which is as fast as BLAST and has the features of BLAST (e.g. robust statistical basis, and effective and reliable search capabilities) for protein sequence search. 3D-BLAST is the first tool to search large protein structures (> 30000) within 3 seconds in the world. We believe that 3D-BLAST will be the most popular tool to elucidate the structural homology by large protein structure database search. The number of accessing this tool exceeds 5,100 from 44 countries and our papers were cited over 13 times since 2007.
Bio-computational Lab – PI: Dr. Jenn-Kang Hwang
- CELLO – protein subcellular localization predictor
- pKNOT – the first knotted protein server
Intelligent Computing Lab – PI: Dr. Shinn-Ying Ho
- We aim to develop various evolutionary computation algorithms and optimization methodologies, and provide user-friendly tools for system optimization. A representative paper is as follows: S.-Y. Ho*, L.-S. Shu and J.-H. Chen, "Intelligent Evolutionary Algorithms for Large Parameter Optimization Problems," IEEE Trans. Evolutionary Computation, vol. 8, no. 6, pp. 522-541, Dec. 2004. (Highly cited article)
- Based on the expertise of intelligent computation, we develop various bio-inspired optimization algorithms for computational proteomics, computational systems biology, computational biology, bioinformatics, etc.
- We establish national/international interdisciplinary collaboration with biologists to investigate systems biology and validate our proposed models.
- We are interested in establishing a user-friendly system of computer-aid vaccine design.
Electrocardiology and Cardiovascular Bioinformatics Lab –PI: Dr. Ten-Fang Yang
- Time Domain and Frequency Domain Signal Analysis in SAECG,
- Time Domain and Frequency Domain Signal Analysis in HRV.
- SAECG research in Normal Taiwanese,
- HRV research in Normal Taiwanese,
- Age, Gender and Race Variations on SAECG,
- Age, Gender and Race Variations on HRV,
- SAECG research on Hemodialysis Chronic Renal Failure Patients,
- HRV research on Hemodialysis Chronic Renal Failure Patients,
- Standard 12-lead ECG research on Heart Diseases,
- VCG and Derived VCG research in Cardiology,
- Parametric Modeling of Signal averaged ECG,
- Electrocardiological evaluation of Sudden Cardiac Death.
Bioinformatics Algorithm Lab– PI: Dr. Chin Lung Lu
- Multiple Sequence Alignment with Constraints (MuSiC, MuSiC-ME, RE-MuSiC)
We are the first to propose the concept of constrained sequence alignment that allows biologists to incorporate their knowledge about structures/functionalities/consensuses of their datasets into sequence alignment. By specifying known functionally, structurally or evolutionarily related residues/nucleotides of the input sequences as constraints, the output of the constrained sequence alignment is an optimal sequence alignment in the condition that the user-specified residues/nucleotides should be aligned together in the alignment, so that the output alignment can more accurately reflect the true biological relationships among the input sequences. In this study, we have first designed an efficient algorithm for computing a constrained alignment of multiple sequences and have also developed a web server, called MuSiC (Multiple Sequence alignment with Constraints), for the online analysis. Using MuSiC, we have successfully located the subsequence fragment of the RNA sequence of SARS that is capable of folding itself into a stable RNA secondary structure with pseudoknot responsible for the replication of SARS viruses (Bioinformatics, 20:2309-2311, 2004). Then we have further developed its memory-efficient version, called MuSiC-ME (Memory-Efficient Multiple Sequence alignment with Constraints), that allows the users to align multiple sequences of length up to several thousand residues (Bioinformatics, 21:20-30, 2005). More recently, we have developed RE-MuSiC by further enhancing the constraint formulation of MuSiC as regular expressions, which is convenient in expressing many biologically significant patterns like those collected in the PROSITE database, or structural consensuses that often involve variable ranges between conserved parts. Experiments demonstrate that RE-MuSiC can be used to help predict important residues and locate evolutionarily conserved structural elements (Nucleic Acids Research, 35:W639-644, 2007).
Figure 1: Three GST (Glutathione S-Transferase) proteins: The structural similarity between these three proteins is very high, but their pairwise sequence identities are extremely low.
Figure 2: The constrained sequence alignment produced by RE-MuSiC, using the pattern of "[ST]-x(2)-[DE]" as the constraint, in which the residues shaded in yellow match the pattern. In addition, the residues in green boxes that correspond to the active sites shared by these three GST proteins are aligned together.
Integrative Systems Biology Lab – PI: Dr. Hsien-Da Huang
- [MicroRNA Regulation: Databases and Tools]
Recent works have demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. In order to facilitate the investigation of microRNA regulation, we developed several biological databases and computational tools in this important field. Six articles in this filed were published in Nucleic Acids Research (2007 SCI Impact = 6.954). miRNAMap was selected as hot research in 2006 NAR Database Issue. miRNAMap was genomics maps for microRNA genes and their targets in metazoan genomes (Nucl Acids Res, 2006, Nucl Acids Res, 2008). ViTa is a database of host microRNA targets on viruses (Nucl Acids Res, 2007). We also survey the literatures to extract the RNA structural motifs and their functions to construct the RegRNA database (Nucl Acids Res, 2006). The RNAMST web server was developed for searching RNA structural homologs (Nucl Acids Res, 2006). RNALogo is designed as a new approach to display structural RNA alignment (Nucl Acids Res, 2008). These databases and tools were cited more than 53 times during last two years.
- [Protein Post-translational Modification: Database and Tools]
Protein Post-Translational Modification (PTM) plays an essential role in cellular control mechanisms that adjust protein physical and chemical properties, folding, conformation, stability and activity, thus also altering protein function. Four articles in this filed were published in Nucleic Acids Research (2007 SCI Impact = 6.954). dbPTM is a comprehensive information repository of protein post-translational modification (PTM) (Nucl Acids Res, 2006). Furthermore, we developed KinasePhos [1.0, 2.0], which is a web tool for identifying protein kinase-specific phosphorylation site (Nucl Acids Res, 2005, 2007, J. Comp Chem 2005). Besides, ProKware was designed as an integrated software for presenting protein structural properties in protein tertiary structures (Nucl Acids Res, 2006). These database and tools were totally cited more than 50 times during last three years.
Computational Chemistry Lab – PI: Dr. Jen-Shiang Yu
- Theoretical coordination chemistry. Theories based on quantum mechanics are beneficial to investigate the characters of multiple bonding between transition metals as well as the reaction mechanisms. Metalloproteins can be simulated by similar approaches.
- Structures and reactions of proteins. Quantum theories are widely used to study the conformational structures, reaction properties and other biological significance of proteins. Applicable methodologies include ab initio methods, density function theories, semi- empirical methods as well as molecular mechanics, and their mathematical hybrids.
- Many Saccharomyces cerevisiae duplicate genes that were derived from an ancient whole-genome duplication (WGD) unexpectedly show a small synonymous divergence (K S), a higher sequence similarity to each other than to orthologues in Saccharomyces bayanus, or slow evolution compared with the orthologue in Kluyveromyces waltii, a non-WGD species. This decelerated evolution was attributed to gene conversion between duplicates. Using ≈300 WGD gene pairs in four species and their orthologues in non-WGD species, we show that codon-usage bias and protein-sequence conservation are two important causes for decelerated evolution of duplicate genes, whereas gene conversion is effective only in the presence of strong codon-usage bias or protein-sequence conservation. Furthermore, we find that change in mutation pattern or in tDNA copy number changed codon-usage bias and increased the K S distance between K. waltii and S. cerevisiae. Intriguingly, some proteins showed fast evolution before the radiation of WGD species but little or no sequence divergence between orthologues and paralogues thereafter, indicating that functional conservation after the radiation may also be responsible for decelerated evolution in duplicates.
- We used pluripotent P19 cells to study the function of microtubule-associated proteins during neuritogenesis. Multi-dimensional protein identification technology (one type of gel-free high throughput proteomics) was performed on microtubule-associated proteins prepared before versus shortly after neurite induction. More than 800 proteins were consistently identified in both proteomes. Surprisingly, when these two proteomes were quantitatively compared, the majority of the proteome remain unchanged. Substantial changes in the microtubule-associated proteome occurred at the level of individual proteins. Based on our proteomic results, we assayed primary neurons using RNA interference to identify a novel inhibitory role for protein TRIM2 in neurite elongation.