BIOGRAPHICAL SKETCH
Provide the following information for the key personnel and other significant contributors in the order listed
on Form Page 2.
Follow this format for each person. DO NOT EXCEED FOUR PAGES.
NAME
POSITION TITLE
Xuefeng Bruce Ling
Sr. Scientist
eRA COMMONS USER NAME
bxling
EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as
nursing, and include postdoctoral training.)
DEGREE
INSTITUTION AND LOCATION
(if
YEAR(s)
FIELD OF STUDY
applicable)
1990
Biochemistry
Fudan University, China
B.S.
UCLA, US
M.A.
1994
Molecular Biology
UCLA, US
Ph.D.
1996
Biological Chemistry
Stanford University, US
Postdoctoral
1996-1998 Computer Science
Postdoctoral
Stanford University Medical Center, US
1996-1998 Medicine/Oncology
Fellow
Leavey School of Business, Santa Clara
2000-2001 Business Administration
University, US
A. Personal statement
The proposed research and the implementing multidisplinary team, headed by Dr. Lu Tian, offer an unparrelled
opportunity to translate cutting edge technologies and breakthroughs in proteomics, machine learning based
biomarker discovery, and modern medicine into a predictive test to overcome the challenges of neonatal
disease. Ever since my interdisplinary postgraduate training in computer science and medicine at Stanford
University, I have been trying to tap the power of high throughput biotechnologies and computational
innovations to advance the therapy and practice of medicine. Through industrial and academic endeavors, I
have proved myself as an experienced team leader, algorithm/software developer, and scientist with a record
of accomplishments in the innovative use of artificial intelligence and high throughput biotechnologies for drug
target identification, drug design and discovery, biomarker discovery/validation, and translational medicine.
Five years ago, I was recruited to Stanford’s ground breaking translational medicine program funded by the
Children’s Health Initiative, which brought together engineers, scientists, and clinicians to collaborate on
biotechnology projects. Sucessful collaborations included various Stanford clinicians resulted in the creation of
a plasma and/or urine diagnostic/prognostic panels for varioius challenging diseases including renal allograft
dysfunctions, Kawasaki Disease, systemic juvenile idiopathic arthritis (sJIA), glioblastoma, and necrotizing
colitis etc. The Tian Lab is part of the Stanford statistics community at Stanford University. Dr. Tian focuses on
novel statistical method development and apply machine learning in clinical science. Dr. Sylvester is the head
of national neonatal disease network, specializing in necrotizling colitis disease research and management.
Therefore, this proposal that combines this cross-functional teams’ expertise in statistical machine learning, the
cutting edge proteomics profiling technology, and years’ of clinical experience has been carefully planned and
solidly positioned to address neonatal disease challenge: a predictive algorithm for high-risk neonatal disease
progression.
B. Positions and Honors
Positions
2007 Senior Scientist, Translational Medicine Program, School of Medicine, Stanford University
2006
Consultant, Biotechnology Core, Lucile Packard Children’s Hospital, Stanford University
2004 - 2005 Director, Research & Development Informatics Amgen San Francisco.
2002 - 2004 Research Director, Tularik Inc.
2001 - 2002 Director, R&D informatics, Tularik Inc.
2000 - 2001 Associate Director, Research & Development, DoubleTwist, Inc.
1999 - 2000 Project manager, Research, Pangea System, Inc.
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Principal Investigator/Program Director (Last, First, Middle):
Burns, Jane C.
1998 - 1999 Computation/Bioinformatics Scientist, Incyte Pharmaceuticals, Inc.
Service
2005 Member, Journal Editorial Board, Cancer Informatics
1997
Member, Medical Advisor Board,National Kidney Foundation of Northern California
Honors
1997 – 1998
Walter Berry Medical Research Award
1997
National Kidney Foundation Research Award
1996
Dean's Fellowship, Stanford University
1992 -1993
University Fellowship, UCLA, CA
1991 - 1992
University Fellowship, University of Iowa, IA
1990 - 1991
University Fellowship, Fudan University, China
1990
Summa cum laude, Fudan University, China
1986 – 1990
University Fellowship, Fudan University, China
C. 16 selected peer-reviewed publications (from 30 publications)
Most relevant to the current diagnostic application development
1) Ling XB, Park JL, Carroll T, Nguyen KD, Lau K, Macaubas C, et al. Plasma profiles in active systemic
juvenile idiopathic arthritis: biomarkers and biological implications. Proteomics. In press.
2) Ling XB, Lau K, Deshpande C, Park JL, Milojevic D, et al. Urine peptidomic and targeted plasma protein
analyses in the diagnosis and monitoring of systemic juvenile idiopathic arthritis. Clinical proteomics. In
press.
3) Ling XB, Mellins ED, Sylvester KG, Cohen, HJ. 2010. Urine peptidomics for clinical biomarker discovery.
Advance in Clinical Chemistry. 51: 181-213.
4) Ling XB, Sigdel, TK, Lau K. Lin Y, Lau I, Schilling J, Sarwal M. 2010. Integrative Urinary Peptidomics in
Renal Transplantation Identifies Novel Biomarkers for Acute Rejection. JASN 21:646-653.
5) Ling XB, Zhou L, Cai M, Wang Q, Lau K, Zhao JJ, Schilling J, Chen L. 2009. Tumor associated proteome
and peptidome analyses for multiclass cancer discrimination. Clinical Proteomics 5:163-169
6) Ling XB, Cohen HJ, Jin J, Lau I, Schilling J. 2009. FDR made easy in differential feature discovery and
correlation analysis. Bioinformatics 25:1461-2.
7) Yang Q, Whitin JC, Ling XB, Nayak N, Cohen HJ, Jin J, Schilling J, Yu TT, and Madan A. 2009. Plasma
biomarkers in a mouse model of preterm labor. Pediatric Research 66:11-6.
8) Liu JJ, Cutler G, Li W., Pan Z., Peng S, Hoey T, Chen L, Ling XB. 2005. Multiclass cancer classification
and biomarker discovery using GA-based algorithms. Bioinformatics 21: 2691-2697.
Additional recent publications of importance to the field
1 ).Allibhai T, DiGeronimo R, Whitin J, Salazar J, Yu,TT, Ling XB, Cohen H, Dixon,P, Madan A. 2009. Effects
of moderate versus deep hypothermic circulatory arrest and selective cerebral perfusion on
cerebrospinal fluid proteomic profiles in a piglet model of cardiopulmonary bypass. J Thorac Cardiovasc
Surg. 138(6):1290-6.
2) Sigdel TK, Ling XB, Lau K, Li L, Schilling J, Sarwal M. 2009. Urinary peptidomic analysis identifies potential
biomarkers for acute rejection of renal transplantation. Clinical Proteomics 5, 103-113.
3) Ling, XB. 2008. High throughput screening informatics. Comb Chem High Throughput Screen. 11(3):24957.
4) Li WX, Li L, Eksterowicz J, Ling XB, Cardozo M. 2007. Significance Analysis and Multiple Pharmacophore
Models for Differentiating P-Glycoprotein Substrates. J. Chem. Inf. Model. 47: 2429-2438.
5) Chen Z, Wang W, Ling XB, Liu JJ, Chen L. 2006. GO-Diff: Mining functional differentiation between ESTbased transcriptomes. BMC Bioinformatics 7: 72.
6) Li S, Cutler G, Liu JJ, Hoey T, Chen L, Schultz PG, Liao J, Ling XB. 2003. A comparative analysis of HGSC
and Celera human genome assemblies and gene sets. Bioinformatics 19:1597-1605.
7) Pei L, Peng Y, YangY, Ling XB, van Eyndhoven WG, Nguyen K, Rubin M, Hoey T, Powers S and Li, J
2002. PRC17, a novel oncogene encoding a Rab GTPase-activating protein, is amplified in prostate
cancer. Cancer Res. 62 (19):5420-4.
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Principal Investigator/Program Director (Last, First, Middle):
Burns, Jane C.
8) Pouliot Y, Gao J, Su Q, Liu G, Ling XB. 2001. DIAN, a Novel Algorithm for Genome Ontological
Classification. Genome Res. 11(10):1766-79.
Software Copyright
1. “MASS-Conductor” - High throughput proteomic biomarker discovery platform. Ling XB
2. Stanford “FDR server” Ling XB
3.“DIAN” - A novel computational algorithm for genome ontological classification. Ling XB
D. Research Support:
Ongoing Research Support
Lucile Park Foundation (Supervisor: Cohen)
10/1/2010 – 2/1/2011
Children’s health initiative (CHI) transition fund currently supports all of Dr. Ling’s salary and benefits such that
100% of his efforts are focused on the translational medicine efforts in Stanford Lucile Park Children’s Hospital.
Pediatric disease biomarker discovery and translational analytic support.
Selected Completed Research Support
Corporate research project (PI: Ling)
1/00-1/01
DoubleTwist, Inc.
Develop high throughput novel algorithms for highthroughput genome ontological classification
Corporate research project (PI: Ling)
1/01-1/04
Tularik Inc.
Develop high throughput computation platform (the Discovery Platform) to enable globally integrated high
throughput small molecule screening in either cell based or biochemical assays.
Corporate research project (PI: Ling)
1/01-1/03
Tularik Inc.
Developed informatics platform for array CGH to screen for genetic lesions in cancer to discover novel cancer
targets
Corporate research project (PI: Ling)
1/04-1/05
Amgen San Francisco
Develop compound property based CSAR/QSAR models to address compound PGP (P-glycoprotein, Efflux
pump) liability in compound brain permeability for CNS programs
Corporate research project (PI: Ling)
1/04-1/05
Amgen San Francisco
Discover cancer targets through the large-scale tumor tissue sequencing and SNP analysis of somatic
mutations in the potential targets of the interest and to explore their implications in cancer
Children’s health initiative (CHI)
Lucille Packard Foundation (PIs: Krensky, Cohen)
1/06-10/09
Develop proteomic (2D gel DIGE and LCMS) platforms to discover diagnostic and prognostic biomarkers for in
urine, plasma and tissue.
Develop high throughput computational platform for feature detection and discovery of discriminative features
in LCMS based biomarker discovery
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