Clinical Focus

  • Emergency Medicine
  • Infectious Diseases
  • Global Health
  • Medical Technology

Academic Appointments

Professional Education

  • Fellowship:Johns Hopkins University, School of Medicine (2004) MD
  • Residency:Johns Hopkins University, School of Medicine (2002) MD
  • Medical Education:University of California, Los Angeles (1999) CA
  • Undergraduate, MIT, MA (1994)
  • Board Certification: Emergency Medicine, American Board of Emergency Medicine (2007)

Research & Scholarship

Current Research and Scholarly Interests

Dr. Yang's research is focused on bridging the translational gap at the interface of molecular biology, engineering, and acute care medicine. The investigative interest of the Yang lab falls within the general theme of developing advanced molecular diagnostic technologies for acute care medicine and is divided into 2 areas: 1) Integrating novel molecular, sensor, and microfluidic technologies into high-content diagnostic system for broad-range pathogen detection and characterization, and 2) discovering epigenetic and transcriptional biomarkers for improved diagnosis and prognosis of critical systemic illnesses.


Postdoctoral Advisees


Journal Articles

  • Trainable high resolution melt curve machine learning classifier for large-scale reliable genotyping of sequence variants. PloS one Athamanolap, P., Parekh, V., Fraley, S. I., Agarwal, V., Shin, D. J., Jacobs, M. A., Wang, T. H., Yang, S. 2014; 9 (9): e109094


    High resolution melt (HRM) is gaining considerable popularity as a simple and robust method for genotyping sequence variants. However, accurate genotyping of an unknown sample for which a large number of possible variants may exist will require an automated HRM curve identification method capable of comparing unknowns against a large cohort of known sequence variants. Herein, we describe a new method for automated HRM curve classification based on machine learning methods and learned tolerance for reaction condition deviations. We tested this method in silico through multiple cross-validations using curves generated from 9 different simulated experimental conditions to classify 92 known serotypes of Streptococcus pneumoniae and demonstrated over 99% accuracy with 8 training curves per serotype. In vitro verification of the algorithm was tested using sequence variants of a cancer-related gene and demonstrated 100% accuracy with 3 training curves per sequence variant. The machine learning algorithm enabled reliable, scalable, and automated HRM genotyping analysis with broad potential clinical and epidemiological applications.

    View details for DOI 10.1371/journal.pone.0109094

    View details for PubMedID 25275518

  • Universal digital high-resolution melt: a novel approach to broad-based profiling of heterogeneous biological samples NUCLEIC ACIDS RESEARCH Fraley, S. I., Hardick, J., Masek, B. J., Athamanolap, P., Rothman, R. E., Gaydos, C. A., Carroll, K. C., Wakefield, T., Wang, T., Yang, S. 2013; 41 (18)


    Comprehensive profiling of nucleic acids in genetically heterogeneous samples is important for clinical and basic research applications. Universal digital high-resolution melt (U-dHRM) is a new approach to broad-based PCR diagnostics and profiling technologies that can overcome issues of poor sensitivity due to contaminating nucleic acids and poor specificity due to primer or probe hybridization inaccuracies for single nucleotide variations. The U-dHRM approach uses broad-based primers or ligated adapter sequences to universally amplify all nucleic acid molecules in a heterogeneous sample, which have been partitioned, as in digital PCR. Extensive assay optimization enables direct sequence identification by algorithm-based matching of melt curve shape and Tm to a database of known sequence-specific melt curves. We show that single-molecule detection and single nucleotide sensitivity is possible. The feasibility and utility of U-dHRM is demonstrated through detection of bacteria associated with polymicrobial blood infection and microRNAs (miRNAs) associated with host response to infection. U-dHRM using broad-based 16S rRNA gene primers demonstrates universal single cell detection of bacterial pathogens, even in the presence of larger amounts of contaminating bacteria; U-dHRM using universally adapted Lethal-7 miRNAs in a heterogeneous mixture showcases the single copy sensitivity and single nucleotide specificity of this approach.

    View details for DOI 10.1093/nar/gkt684

    View details for Web of Science ID 000325776600006

    View details for PubMedID 23935121

  • Advances in microfluidic PCR for point-of-care infectious disease diagnostics BIOTECHNOLOGY ADVANCES Park, S., Zhang, Y., Lin, S., Wang, T., Yang, S. 2011; 29 (6): 830-839


    Global burdens from existing or emerging infectious diseases emphasize the need for point-of-care (POC) diagnostics to enhance timely recognition and intervention. Molecular approaches based on PCR methods have made significant inroads by improving detection time and accuracy but are still largely hampered by resource-intensive processing in centralized laboratories, thereby precluding their routine bedside- or field-use. Microfluidic technologies have enabled miniaturization of PCR processes onto a chip device with potential benefits including speed, cost, portability, throughput, and automation. In this review, we provide an overview of recent advances in microfluidic PCR technologies and discuss practical issues and perspectives related to implementing them into infectious disease diagnostics.

    View details for DOI 10.1016/j.biotechadv.2011.06.017

    View details for Web of Science ID 000296821900024

    View details for PubMedID 21741465

  • Continuous dielectrophoretic bacterial separation and concentration from physiological media of high conductivity LAB ON A CHIP Park, S., Zhang, Y., Wang, T., Yang, S. 2011; 11 (17): 2893-2900


    Biological sample processing involves purifying target analytes from various sample matrices and concentrating them to a small volume from a large volume of crude sample. This complex process is the major obstacle for developing a microfluidic diagnostic platform. In this study, we present a microfluidic device that can continuously separate and concentrate pathogenic bacterial cells from complex sample matrices such as cerebrospinal fluid and whole blood. Having overcome critical limitations of dielectrophoretic (DEP) operation in physiological media of high conductivity, we utilized target specific DEP techniques to incorporate cell separation, medium exchange, and target concentration into an integrated platform. The proposed microfluidic device can uptake mL volumes of crude biological sample and selectively concentrate target cells into a submicrolitre volume, providing ~10(4) fold of concentration. We designed the device based on the electrokinetic theory and electric field simulation, and tested the device performance with different sample types. The separation efficiency of the device was as high as 97.0% for a bead mixture in TAE buffer and 94.3% and 87.2% for E. coli in human cerebrospinal fluid and blood, respectively. A capture efficiency of 100% was achieved in the concentration chamber. With a relatively simple configuration, the proposed device provides a robust method of continuous sample processing, which can be readily integrated into a fully automated microfluidic diagnostic platform for pathogen detection and quantification.

    View details for DOI 10.1039/c1lc20307j

    View details for Web of Science ID 000293651100012

    View details for PubMedID 21776517

  • Molecular methods for pathogen detection in blood LANCET Lin, S., Yang, S. 2010; 375 (9710): 178-179
  • PCR-based diagnostics for infectious diseases: uses, limitations, and future applications in acute-care settings LANCET INFECTIOUS DISEASES Yang, S., Rothman, R. E. 2004; 4 (6): 337-348


    Molecular diagnostics are revolutionising the clinical practice of infectious disease. Their effects will be significant in acute-care settings where timely and accurate diagnostic tools are critical for patient treatment decisions and outcomes. PCR is the most well-developed molecular technique up to now, and has a wide range of already fulfilled, and potential, clinical applications, including specific or broad-spectrum pathogen detection, evaluation of emerging novel infections, surveillance, early detection of biothreat agents, and antimicrobial resistance profiling. PCR-based methods may also be cost effective relative to traditional testing procedures. Further advancement of technology is needed to improve automation, optimise detection sensitivity and specificity, and expand the capacity to detect multiple targets simultaneously (multiplexing). This review provides an up-to-date look at the general principles, diagnostic value, and limitations of the most current PCR-based platforms as they evolve from bench to bedside.

    View details for Web of Science ID 000221799100020

    View details for PubMedID 15172342

Stanford Medicine Resources: