Eric Snyder Email & Phone Number

Phoenix, Arizona Area

Applying statistics, machine learning and software development to optimize the recovery process for non-ferrous metals in mining industry.

Tempe, Az

Developed a Python application to build and optimize diagnostic classifiers based on an evaluation of a subject’s humoral immune response using peptide microarrays. The application begins by extracting and normalizing feature intensities from chips processed with sera from study participants with specific clinical presentations (factors). Subjects are grouped by factor (e.g., case and control) and each feature is evaluated by t-test to assess the significance of the differential immune response. Peptides are ranked by p-value and a subset extracted for use as potential diagnostic marker panel. To evaluate this potential, array data is used to train an SVM or naïve Bayesian classifier to differentiate between subjects in one group versus another. A cross-validation procedure is employed to obtain an accurate and realistic assessment of the classifier’s generalization performance. The optimal choice of classifier, normalization method, p-value cutoff, peptide count and other model parameters must be determined heuristically. By putting all aspects of classifier construction, optimization, training and testing into a single application, it is possible to systematically explore the parameter space around each classifier candidate. This method has been used to build diagnostic systems for several cancers (including breast, lung and pancreas) and numerous infectious diseases, often with unprecedented accuracy.

Greater Atlanta Area

Senior Business Analyst, contractor for the Centers for Disease Control and Prevention; Office of Public Health Scientific Services; Center for Surveillance, Epidemiology, and Laboratory Services; Division of Health Informatics and Surveillance (HHS/CDC/OPHSS/CSELS/DHIS).• Collected, organized and documented a detailed software requirements specification (SRS) for EPI INFO™ version 7.2, a suite of programs to support epidemiological studies. The application enables: the creation of sophisticated data collection questionnaires, suitable for field use on smartphones and other portable electronics; data storage and integration using RDBMS platforms and common file formats; data processing, recoding and analysis using descriptive and inferential statistics including multiple linear and logistic regression, KM survival curves, proportional hazards, complex sampling strategies and social (interaction) network analysis; integration with geographical information allowing subjects and other relevant features to be located on dynamic maps and overlaid with demographic, socio-economic or other reference data.• The SRS, based on the ISO/IEEE-830 and -29148 standards, is aimed at promoting and facilitating collaborative and 3rd-party development of the open source/GPL EPI INFO™ software. Requirements are published online using Atlassian Confluence and integrated with JIRA, an Agile-oriented task-tracking system.

Greater Atlanta Area

Senior Scientist, Bioinformatics, contractor for the Center for Disease Control and Prevention, Office of Infectious Diseases, National Center for Immunization and Respiratory Diseases, Influenza Division, Office of Director• Lead developer responsible for design and implementation of sequence analysis pipeline services for Influenza Surveillance Data Management System (ISDMS), an in-house database and analysis resource for influenza sequence, annotation and metadata.• Primary annotation program used a database of 92 HMMs based on SME-derived, lineage-specific segment groups to identify influenza type (A or B), segment (1-8) and lineage of sequence, then performs NA-to-AA spliced alignment to known segment proteins to determine precise CDS coordinates. Also created BLAST-based programs for identifying segments from 2009 H1N1 pandemic strain and recently-identified H1 and H3 variants.• Conceived of and designed JSON Feature Format (JFF), a standardized web-service-friendly format for sequence features and metadata, used by all ISDMS pipeline programs. Wrote Perl libraries to manipulate, validate and load JFF data into BioSQL databases (such as ISDMS).• Development mechanism for synchronizing ISDMS with GenBank using NCBI eUtilities. Parsed free-text host data and mapped to NCBI taxonomy. Wrote script to query ISDMS and efficiently build non-redundant AA & NT BLAST databases using MD5 hash keys.

2115 East Jefferson St, Rockville, Md 20852-4902

Senior Scientist, Bioinformatics, contractor for the Data Coordination Center (DCC) of theCancer Genome Atlas project (TCGA), a join program of the National Cancer Institute (NCI) andNational Human Genome Research Institute (NHGRI) aimed at identifying the molecular basis ofcancer using high-throughput genome analysis technologies.* Acted as POC for the Biospecimen Core Resource centers to coordinate the development and evolution of the XML schema representing clinical information and biospecimens.* Wrote and documented software to assemble, validate and submit data to the DCC and other NIH databases; supplied detailed requirements for the 2 -generation DCC database and UI.* Represented the DCC on the Analysis Working Groups (AWGs) for acute myeloid leukemia (AML), stomach and esophageal carcinoma, and ovarian serous cystadenocarcinoma, managing data freezes and ensuring availability of all clinical and molecular data.

Blacksburg, Virginia, United States

Bioinformatics and genomics research; development of algorithms and computational pipelines for genome annotation; annotation of microbial genomes; meta-analyses: orthology, phylogenetics; contributed to development of online resource for microbial genomics to support biomedical research on pathogen counter-measures.

Used statistical genetics to identify genes associated with human obesity.Organized and maintained the Obesity Gene Map Database, a database of loci (genes and markers) associated with obesity-related phenotypes.Created software to facilitate the interpretation of Serial Analysis of Gene Expression (SAGE) studies, a sequence-based method to identify and quantify mRNA species to measure gene expression.

Ph.D., Molecular, Cellular And Developmental Biology

Activities and Societies: Chairman, Graduate Student Symposium Graduate Student Representative to Faculty Affairs CommitteeGraduate Work.

B.A., Chemistry And Mcd Biology (Double Major)

Department of Chemistry and Biochemistry, University of Colorado, Boulder, CO (Mentor: Prof. Joseph J. Falke) • Performed fluorometric.

Psychology, Chemistry

Department of Psychology, The Johns Hopkins University, Baltimore, MD (Mentors: Dr. Priscilla Kehoe & Prof. Elliott M. Blass) • Used.