Welcome to Yang, Jinn-Moon's Home Page
The World of Drug
Discovery (simmap), Function (Structural) Bioinformatics
And Systems Biology (Interface Family).
Let dreams COME True.
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News and Highlights
Ph.D.
students, Jhang-Wei Huang (黃章維) and Kai-Cheng Hsu (許凱程), started Postdoctoral Fellow at
BioXGEM (2010 and 2011).
Ph.D.
student, Chi-Hua Tung (董其樺), started Assistant Professor at Department
of Bioinformatics, Chung Hua University (2010).
Ph.D.
student, Chun-Chen Chen (陳俊辰), started Postdoctoral
Fellow at Centers of Disease Control (CDC, 疾病管制局), 2009.
Co-advised Ph.D. student,
Yen-Wei Chu (Dr. 朱彥煒), started Assistant Professor at Institute of
Bioinformatics, National Chung Hsing University, Aug. 2008.
We
got a 5-year NHRI(國衛院) project (2011/1-2015/12: 分子間藥理作用介面家族應用在磷酸化酵素-藥物-疾病網絡與機制之研究)
We
got a 3-year NSC(國科會) NRPB project (生技醫藥國家型科技計畫) (2011/5-2014/4:
Structure-based polypharmacology for discovering and optimizing new
antibiotics以結構為基礎之多標靶藥理用於新型抗生素之開發與最佳化)
We
got a 3-year NSC(國科會) Interdisciplinary
Bioinformatics Project (跨領域生物資訊) (2011/8-1014/7: Drug-target network and structure-based systems
biology for cancers and neurological disorders)
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[GEMDOCK and SiMMap: Drug Discovery] The total number of citations for
"drug discovery" papers, GEMDOCK and its applications, was over 450.
Based on the ability and flexibility of GEMDOCK, we have successfully
cooperated over seven Labs, such as NHRI, Prof
Hsu TA (Inhibitors of avian influenza
virus neuraminidases); Prof. Wang WC
(Inhibitors of helicobacter
pylori shikimate kinase), Prof MAO JT (secondary
vitamin D3 binding site of milk beta-lactoglobulin); Prof. Yang YS (Substrates of sulfotransferase
and hydantoinase);
Prof. Yuan CJ
(Substrates of
amine oxidase); Prof.
Yang YL (Inhibitors of envelop
protein of dengue virus); and Prof. Liao KW
(peptide-binding motifs of MHC class
I). We also cooperated with Prof. Hsu on
data fusion for virtual screening.
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[PCFamily, PPISearch and 3D-partner: Systems
Biology]
We derive a new concept, called the 3D-domain interologs
which is similar to interologs. The 3D-domain
interologs is defined as Domain a (in chain A)
interacts with domain b (in chain B) in a known 3D complex,
their inferring protein pair A' (containing domain a ) and B'
(containing domain b ) in the same species would be likely to
interact with each other if both protein pairs (A' and A as well as proteins
B and B') are homologous.
3D-partner (3D-partner: a
web server to infer interacting partners and binding models) and PCFamily, published in Nucleic
Acids Research, predicts interacting partners and binding models by using
3D-domain
interologs through structure complexes and a knowledge-based scoring
function. These homologous structures and interacting partners were evaluated
by a new scoring function which considered steric and special-bond matrices
but also the interfacial stability (couple-conserved residue score and
template similarity).
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[3D-BLAST and fastSCOP: Structural
Genomics]
Our paper, Kappa-alpha plot
derived structural alphabet and BLOSUM-like substitution matrix for fast
protein structure database search, was published in Genome Biology. In this paper, we
present a novel protein structure database search tool, 3D-BLAST, that is useful for analyzing novel
structures and can return a ranked list of alignments. This tool has the
features of BLAST (for example, robust statistical basis, search effective
and reliable search capabilities) by using a kappa-alpha (k, a) plot derived
structural alphabet and a new substitution matrix. 3D-BLAST searches over
12,000 protein structures in 1.2 seconds and yields good results in zones
with low sequence similarity.
fastSCOP (fastSCOP: a
fast web server for recognizing protein structural domains and SCOP
superfamilies, published in NAR) rapidly identifies the structural domains
and determines the evolutionary superfamilies of a query protein structure.
fastSCOP uses 3D-BLAST to scan quickly a
large structural classification database and MAMMOTH, a detailed structural
alignment tool, is adopted to refine domain boundaries and to identify
evolutionary superfamilies.
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[FCEA: Bio-inspiration Computation
Methods]
The total
cited number of our papers, bio-inspiration computation methods (called FCEA)
and their applications, was over 1000.
FCEA combines adaptive mutations and family competition to solve
optimization problems in widely differing fields (e.g. function optimization,
constrained optimization, and thin-film design, neural networks) and
Bioinformatics applications (e.g. protein-ligand interactions,
protein-protein interaction sites, protein folding, Microarray analysis, and
QSAR model).
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