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Dr. Kwoh Chee Keong, PBM PhD,
DIC, MSc(ISE), Beng(EE), PGDIG, Senior
Member, IEEE Senior
Member IES Life
Member ICAAS Member
AMBIS Deputy Executive Director PaCE@NTU Centre
for Professional and Continuing Education 60
Nanyang Drive, SBS-01s-50, Singapore 637551 T: +65
6904 2056 (PaCE@NTU) School
of Computer Science and Engineering Block
N4, Level 2, Section A, Room 29 Nanyang Avenue, Singapore 639798 T: +65
6790 6057 (SCSE-CoE) F: +65
6792 6559 W:
https://personal.ntu.edu.sg/asckkwoh/
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I think the
nicest, most sincere compliments that I have received are those from my
students and people I did not expect.
Notes from
Students and Friends
HONORS AND AWARDS
Public
Service Medal (National Day Award)
National Day Awards 2008, The Public
Service Medal (PBM) http://www.pmo.gov.sg/NationalHonoursandAwards/Pingat+Bakti+Masyarakat+(The+Public+Service+Medal).htm ,
conferred by the President of Singapore, Mr S R Nathan
Ministry
of Education Long Service Medal (National Day Award) 2016
I am looking for a versatile, highly motivated Research Fellow/Pos-doc
PhD candidates. The successful candidates will build on the ongoing research directed
and will help define and explore this exciting area of research.
Applicants must have a strong background in
Computer Science and/or closely related areas (e.g. Mathematics, Computer Science,
Bioinformatics, Statistics and Physics) and excellent skills in both written
and spoken English, as the working language of the Faculty is English.
For PhD application, please visit the Graduate
Studies by Research at NTU before writing. Please note that PhD program is a very intensive program and the applicant
must have a strong interest, strong analytical
mind, technically sound in the area of data mining, learning theory, algorithms
and computer programming. You must be highly independent with good initiatives
and aspire to publish in top-tier journals. If you are interested and suitable,
Enquiries about these vacancies can be sent to asckkwoh@ntu.edu.sg (the deadlines are
flexible) with your CV, your proposed
research area with at least 3 references (either your own publications or
papers that inspired you to do research).
My
main interests lie in our desire to making sense of big heterogeneous data for
real application in engineering, life science, and medical.
High throughput
biological measurements and experiments in life science and healthcare have
resulted in the explosion of data available from sequencing and micro-arrays,
ChIP-Microarrays (ChIP-chip). This has led to the interdisciplinary science
called Bioinformatics. Which use Data Science in solving biological and life
science problems.
Meta-learning is where automatic
learning algorithms are applied to
meta-data about machine learning experiments. The main goal is to use meta-data
to understand how automatic learning can become flexible in solving different
kinds of learning problems and enrich the knowledge discovered. Coupled with
ensemble methods that that integrates results of multiple predictive methods
into one system, these approach has found to be instrumental in improving predictive performance. Application
of this approach has been widely used in big data such as bioinformatics and
medical informatics. An example includes multiple kernel learning for heterogeneous data fusion and sparse learning in genome-wide association study (GWAS), and drug-target interaction
prediction.
CovalentDock
Cloud: a web server for automated covalent docking
Covalent binding is an important
mechanism for many drugs to gain its function. We developed a computational algorithm
to model this chemical event and extended it to a web server, the CovalentDock Cloud, to make it accessible directly online
without any local installation and configuration. It provides a simple yet
user-friendly web interface to perform covalent docking experiments and
analysis online.
Software
for Accelerating Autodock Vina
Quickvina: This project
aims at accelerating Autodock Vina, a program for
protein-ligand docking. The main idea is to skip some of the local searches
which are not promising in finding a
better solution.
Quick Vina 2 is a
fast and accurate molecular docking tool, attained at accurately accelerating AutoDock Vina. It was tested against 195 protein-ligand complexes that compose the core
set of the 2014 release of the PDBbind using default
exhaustiveness level of 8, QVina 2
successfully attained up to 20.49-fold acceleration over Vina.
1.
PUDI (2013) - a Positive-Unlabeled (PU) learning based method aiming to address the
problem of disease gene identification
1.
CACHET- Discovery of
Protein Complexes with Core-Attachment Structures from TAP Data
2.
COACH- COre-AttaCHment based Complex Mining
1.
CovalentDock
Cloud (2013) - This web server allows the researchers and
scientists to perform protein-ligand covalent docking.
2.
CovalentDock:
Automated covalent docking with parameterized covalent linkage energy
estimation and molecular geometry constrains
3.
QuickVina: Accelerating AutoDock Vina Using
Gradient-based Heuristics for Global Optimization
MY GRANTS
·
Computational Virulence Model
with Functional Information for Influenza Viruses
·
Methodological Investigation
for Automatic Detection of Primary Angle Closure Condition (PAC) and PAC
induced Glaucoma
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Bioinformatics Algorithms
for Detecting Genetic and Epigenetic Determinants of Meiotic Recombination
Hotspots from Genomic Data
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Whole genome sequencing,
single nucleotide polymorphisms, electron microscopy, Acinetobacter
baumannii, lipopolysaccharide
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Collaborative Research
Programme On Bioinformatics Algorithms And Tools
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Structural Analysis and Characterisation of Protein Complexes
·
Genomic analysis and
development of a new multilocus variable-number
tandem-repeat analysis - a scheme for
molecular epidemiological typing of Acinetobacter baumannii
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Core-Attachment Based Mining
For Protein Complexes & Small molecule
·
Interactions
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Characterization of novel
extracellular proteins produced by a newly-isolated
strain of Bacillus subtillis.
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Improved Design via
Evolutionary Algorithms
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Protein binding hotspots are
water-free?
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Analysis of Past DRG data
for the study of LOS for better utilization of Hospital Resources
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Data Warehousing and Data
Mining Analysis of Staphylococcus Aureus
·
A novel approach for inter-
to intra- network analysis of genetic
diseases using high-throughput data
·
Neural Systems modelling with functional MRI
·
SCE incubator proposal for
“Evolutionary and Complex Systems Lab”
·
The Application of ultrasound-based augmented reality with the
directional vacuum-assisted breast biopsy device in the treatment of breast
cancer
·
Distributed Diagnosis and
Home Healthcare (D2H2)
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Development of a robotic
semi-automated remote handling system for radioiodine dispensing
·
Functional MR Time-Series
Analysis
·
Augmented Reality for
Prosthesis Cup Placement
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Robotic Skull Based Surgery
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Cardiovascular and
Respiratory Systems' Signal Simulation, Processing and Analysis for ICU, OR and
Telemedicine Applications.
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Strategic research: Interventive augmented reality for medical applications.
·
Surgeon Assistant Robot for
a Selected urological disorder.
MY GRADUATE STUDENTS
·
Pan
Hong – DNA methylation biomarkers of personal disease risk (PhD, 2012)
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Luay
Aswad - A molecular basis of the 5-gene breast tumour
aggressiveness grading signature (AGS) and its network – PhD, (2012 -)
·
Han
Xu - Constructing the Semantic Web for Biomedical Literature (PhD, 2011 - )
·
Ouyang
Xuchang - Automated and Accelerated Covalent Docking and Covalent Virtual
Screening (PhD, 2010–)
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Thidathip
Wongsurawat - Computational Analysis and Prediction of Specific Genomic Regions
Forming R-loop Structure and Chromosomal Variations Associated with Cancer - (PhD, 2015)
·
Zhang
Zhou - Knowledge Discovery In Post Genome-Wide Association Study For Glaucoma
(PhD, 2015)
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Su
Tran To Chinh - Improving the Discrimination of Near-Native Complexes for
Protein Rigid Docking by Implementing Interfacial Water into Protein Interfaces
(PhD, 2015)
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Yang
Peng - Computational Approaches for Disease Gene Identification (PhD, 2014)
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Wu
Min - Mining Protein Complexes From Protein Interaction Data (PhD, 2012)
·
Zhang
Tianyou - Contact Network Based Framework For Infectious Disease Interventions
(PhD, 2015)
·
Stephanus
Daniel Handoko - Constrained-Oriented Refinement-Efficacious Memetic Algorithms
for Efficient Optimization of Computationally-Expensive Problems (PhD, 2014)
·
Adrianto
Wirawan - Whole-Genome Discovery Of Transcriptional Regulator Binding Sites
(PhD, 2011)
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Zhang
Guanglan- Computational Epitope-Driven Vaccine Design (PhD, 2008)
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Zheng
Yun- Design Of Gene Expression Networks From Microarray Data (PhD, 2006)
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Zhao
Ying- Efficient Model And Feature Selection For SVM In Biomedical Data Analysis
(M Eng, -2004)
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Zhao
Jianhui- Human Animation from Motion
Recognition, Analysis and Optimisation ( PhD, 2003)
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Chen
Yintao - Image Processing For Ultrasound Guidance System In Breast Lump
Operation (M Eng, 2002)
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Wang
Yan - Image-Based Indexing And Retrieval Of Trademark Logos, (M Eng, 2001)
·
Veena
Mohan Bhajammanavar - Image Processing Of The Digital
Mammogram For Segmentation And Characterization Of Microcalcifications,
(M Eng, 2000)
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Misra
Sabita - Time Series Analysis Of ECG For Detection Of Premature Ventricular
Contraction (M Eng, 2000)
·
Zou
Qingsong - Object-Based Volume
Visualisation For Medical Imaging (PhD, 2001)
Planned and lectured subjects in
GRADUATE ADVISORS: Prof
Duncan Fyfe Gillies - Professor of Biomedical Data Analysis, Department of
Computing, Imperial College London
My PhD thesis Probabilistic
Reasoning From Correlated Objective Data, University of London, Imperial
College
From Google Scholar
https://scholar.google.com.sg/citations?hl=en&user=jVn0wDMAAAAJ&view_op=list_works&sortby=pubdate
Computational
approaches for detecting protein complexes from protein interaction networks:
a survey X
Li, M Wu, CK Kwoh, SK Ng BMC
genomics 11 (1), S3 |
2010 |
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A core-attachment based
method to detect protein complexes in PPI networks M
Wu, X Li, CK Kwoh, SK Ng BMC
bioinformatics 10 (1), 169 |
2009 |
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AL
Teh, H Pan, L Chen, ML Ong, S Dogra, J
Wong, JL MacIsaac, SM Mah, ... Genome
research, gr. 171439.113 |
2014 |
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Drug–target interaction
prediction by learning from local information and neighbors JP
Mei, CK Kwoh, P Yang, XL Li, J Zheng Bioinformatics
29 (2), 238-245 |
2012 |
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Augmented reality
systems for medical applications SL
Tang, CK Kwoh, MY Teo, NW Sing, KV Ling IEEE
engineering in medicine and biology magazine 17 (3), 49-58 |
1998 |
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Positive-unlabeled
learning for disease gene identification P
Yang, XL Li, JP Mei, CK Kwoh, SK Ng Bioinformatics
28 (20), 2640-2647 |
2012 |
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The safety issues of
medical robotics B
Fei, WS Ng, S Chauhan, CK Kwoh Reliability
Engineering & System Safety 73 (2), 183-192 |
2001 |
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Inferring
gene-phenotype associations via global protein complex network propagation P
Yang, X Li, M Wu, CK Kwoh, SK Ng PloS one 6 (7), e21502 |
2011 |
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Feasibility structure modeling: an effective chaperone for
constrained memetic algorithms SD
Handoko, CK Kwoh, YS Ong IEEE
Transactions on Evolutionary Computation 14 (5), 740-758 |
2010 |
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Applying the clonal selection
principle to find flexible job-shop schedules ZX
Ong, JC Tay, CK Kwoh International
Conference on Artificial Immune Systems, 442-455 |
2005 |
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X
Ouyang, S Zhou, CTT Su, Z Ge, R Li, CK Kwoh Journal
of computational chemistry 34 (4), 326-336 |
2013 |
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CBESW: sequence
alignment on the playstation 3 A
Wirawan, CK Kwoh, NT Hieu, B Schmidt BMC
bioinformatics 9 (1), 377 |
2008 |
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GL
Zhang, N Petrovsky, CK Kwoh, JT August, V Brusic Immunome research 2 (1), 3 |
2006 |
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Using hidden nodes in
Bayesian networks CK
Kwoh, DF Gillies Artificial
intelligence 88 (1-2), 1-38 |
1996 |
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Review of tandem repeat
search tools: a systematic approach to evaluating algorithmic performance KG
Lim, CK Kwoh, LY Hsu, A Wirawan Briefings
in bioinformatics 14 (1), 67-81 |
2012 |
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T
Wongsurawat, P Jenjaroenpun, CK Kwoh, V Kuznetsov Nucleic
acids research 40 (2), e16-e16 |
2011 |
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Fast leave-one-out
evaluation and improvement on inference for LS-SVMs Z
Ying, KC Keong Pattern
Recognition, 2004. ICPR 2004. Proceedings of the 17th International … |
2004 |
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On the two-level hybrid
clustering algorithm EY
Cheu, C Keongg,
Z Zhou International
conference on artificial intelligence in science and … |
2004 |
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Outlining the prostate
boundary using the harmonics method CK
Kwoh, MY Teo, WS Ng, SN Tan, LM Jones Medical
and Biological Engineering and Computing 36 (6), 768-771 |
1998 |
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Ensemble positive unlabeled
learning for disease gene identification P
Yang, X Li, HN Chua, CK Kwoh, SK Ng PloS one 9 (5), e97079 |
2014 |