David Yang PhD

Biostatistics & Bioinformatics

  • PhD, Biostatistics, UCLA

  • MS, Biomedical Engineering

  • BS, Mathematics


As a doctoral graduate from UCLA – Dept of Biostatistics (2002), Dr. Yang has primarily worked as a Principal Investigator in developing data & computation solutions for biostatistics, bioinformatics and health information technologies (HIT). He has developed Bayesian inferential methods to serve various needs in Evidence-Based Medicine and in Personalized Medicine. This includes Markov-Chain Monte Carlo (MCMC) algorithms for linear regression models with missing covariates (Yang, Belin, and Boscardin, 2005) , and for incomplete longitudinal data analysis (Yang, Li, & Shoptaw, 2008; Li, Yang, & Wu, 2007; Yang et al, 2007; Yang & Shoptaw, 2005), parametric and semi-parametric hierarchical modeling methods for profiling/ranking healthcare providers (Yang et al, 2013), and an integrative Bayesian variable selection (iBVS) strategy for biomarker discovery with informative priors (Peng, et al., 2013). Recently, funded by National Institutes of Health (NIH), he is leading a team at Bayessoft to develop a set of software tools for EMA (ecological momentary assessment) and PHM (Personal Health Management) over the Cloud Computing and iOS/Android platforms. Dr. Yang is the Director of Consulting Services.

Joseph Wiemels PhD

Transfer Epidemiology

  • PhD, Environmental Health Services, UC Berkley

  • BA, Biology, Kenyon College

Joseph Wiemels is a renowned Cancer Epidemiologist conducting research on molecular and genetic epidemiology and etiology of childhood leukemia, adult and child brain cancer, adult meningioma, skin, and pancreatic cancer. Since 2000 Dr. Wiemels has been a faculty member at UCSF, conducting research on the molecular and genetic epidemiology and etiology of childhood leukemia and adult brain cancer. Currently, Dr. Wiemels is working with David Yang in developing a series of biologically-based Bayesian strategies for molecular biomarker discovery from integrated genomics analyses, (e.g., global genetic polymorphism, gene expression, and DNA methylation measurements on the same series of subjects in the CCLS). Implicit for these analyses is an intelligent biological annotation of the genome so that relevant features for a disease (in this case childhood B-cell leukemia) are readily apparent. His research involves collection and analysis of geographical data and analysis of the clustering of cancer cases in populations and association with sources of environmental contamination. As an experienced scientist, Dr. Wiemels assists Dr. Yang to ensure the scientific soundness of Bayessoft’s software product development and consulting services in Biostatistics and Bioinformatics.

Jennifer Wang PhD

Bioinformatics

  • PhD, Bioinformatics,
    Bejing University of Technology

  • MS, Computer Science

  • BS, Chemical Science

Jennifer received a B.S. in Chemical Engineering in 1991, a MS in Computer Science in 2003 and a Ph.D. in Bioinformatics in 2008. Her Ph.D. emphasis was “Pattern Recognition and Artificial Intelligence” and published her dissertation on “Analysis of Cancer Gene Expression Profile with Intelligent Computing Technology.” Her work experience has covered the private sector, governmental and academic/ medical. She was awarded a postdoctoral fellowship at the Lombardi Comprehensive Cancer Center at Georgetown University in 2009 researching genomic, transcriptomic, proteomic and metabolomics biomarker discovery in breast, prostate and liver cancers along with pathways/ network analysis and identification with machine learning and text-mining techniques. At Bayessoft she was responsible for a study regarding genetic and environmental interaction as they relate to specific diseases, gene and protein network modeling research, and Omics data modeling.

Brad Ander PhD

Bioinformatics

  • PhD, Physiology, University of Manitoba

  • BS, Biochemistry

Brad Ander is a laboratory-trained scientist with over fifteen years of research experience. His research interests include ischemia/reperfusion injury, neurodevelopmental and neurodegenerative disorders, and computer learning algorithms. He has extensive experience with complete workflows from study design and sample preparation through analysis and interpretation of experiments. Dr. Ander’s background in biochemistry, cardiac electrophysiology, and neuroscience helps lay a strong foundation across diverse biological domains that form his expertise in a systems biology approach to making sense of large and complex data sets.

Cloe Lin

Lead Programmer

  • MS, Statistics,
    University of Memphis, Tenessee

  • BE, University of Finance and Economics (Minor in Statistics), China

Chloe Lin has a master degree in statistics and over 10 years experience in pharmaceutical, biotech, and medical device industries. Ms. Lin's has a strong expertise in statistical programming and analysis of phase I, II, III, and IV clinical trials. Her main therapeutic focus of experience are Oncology, Psychiatry, and Infectious Diseases while managing the statistical programming outputs of submissions to both EMA and FDA. Her project management/leadership skills are excellent for meeting tight timelines with high quality reports.

Edward Lin

Application Architect

  • MS, Computer Science, Marquette University

Mr. Lin obtained a Masters from Marquette University in Computer Science in 2001. He has 16 years of experience with expertise in software development, network communication and business intelligence related to data warehouse projects. He has worked as a chief developer for CIBMTR, the world’s largest Bone Marrow Transplant data collection center, and developed multiple Windows and web based data collection and processing application for CIBMTR data warehouse. He is a certified developer and network engineer for Microsoft, Sun, and Cisco.