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Layer, Ryan Matthew

Assistant Professor

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Research

research overview

  • Ryan Layer develops algorithms to decipher large genomic datasets, engaging computational tools to solve biological problems. During his graduate studies, Dr. Layer began pursuing projects in the area of computational genomics. He developed two novel algorithms for analyzing large genomic datasets. The Binary Interval Search (BITS) algorithm quickly quantifies the relationships between different genomic features, and the LUMPY software package characterizes structural variation within populations. These tools are now used to identify pathogenic mutations in many different human diseases. Through innovative software, Dr. Layer enables researchers to find quantitative relationships in massive genomic datasets and better understand disease traits.

keywords

  • Algorithms for human genome interpretation, Parallel and distributed architectures, Succinct data structures, Structural variation, Cancer genomics, Population genetics, Applications of genomics to clinical care

Publications

selected publications

Teaching

courses taught

  • CSCI 2830 - Special Topics in Computer Science
    Primary Instructor - Fall 2019 / Fall 2020
    Covers topics of interest in computer science at the sophomore level. Content varies from semester to semester. Does not count as Computer Science credit for the Computer Science BA, BS or minor. May be repeated up to 9 total credit hours.
  • CSCI 3104 - Algorithms
    Primary Instructor - Spring 2019 / Spring 2022 / Spring 2023
    Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy algorithms, dynamic programming, linear programming, graph algorithms, problems in P and NP, and approximation algorithms. Same as CSPB 3104.
  • CSCI 4118 - Software Engineering for Scientists
    Primary Instructor - Fall 2022 / Fall 2023
    Learn the core principles of software engineering to develop scientific software that is robust and reproducible. This class targets quantitative scientists in any discipline who have programming skills (any language) and want to use software to further their research. We cover version control, testing, benchmarking, data structures, algorithms, and pipelines. Instructor approval is required for CS majors and CS minors. Recommended prerequisites: ASEN 1320 or CSCI 1200 or CSCI 1300 or CSCI 2275 or ECEN 1310 or INFO 1201 and knowledge of a programming language, preferably Python. Degree credit not granted for this course and CSCI 6118.
  • CSCI 4830 - Special Topics in Computer Science
    Primary Instructor - Spring 2024
    Covers topics of interest in computer science at the senior undergraduate level. Content varies from semester to semester. Only 9 credit hours from CSCI 4830 and/or CSCI 4831 can count toward Computer Science BS or BA.
  • CSCI 4950 - Senior Thesis
    Primary Instructor - Fall 2021 / Spring 2022 / Fall 2024
    Provides an opportunity for senior computer science majors to conduct exploratory research in computer science as an option for the capstone requirement. Department enforced prerequisites: 35 hours of Computer Science coursework including Foundation courses, Upper-Division writing, CS GPA 3.0. Department consent required, contact academic advisor for details. May be repeated up to 8 total credit hours.
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