University Of Washington Computational Biology PHD

Last Updated on December 28, 2022

The  University Of Washington Computational Biology Department  is home to a wide array of computational researchers. From genome researchers to developers, physicists and statisticians, they are all using computers to better understand the functions of human cells.

Is there anything else you need to learn about University Of Washington Computational Biology PHD? If so, you need not be concerned because the following article will provide the information to answer your questions.

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University Of Washington Computational Biology PHD

The goal of the Computational and Systems Biology Program is to train the next generation of scientists in technology intensive, quantitative, systems level approaches to molecular biology. We aim to graduate students who are as comfortable operating the latest high end instrumentation as they are manipulating the mathematical formalisms that are required to make sense of their data. It is our hope that the students who join the Computational and Systems Biology Program will apply these approaches to unraveling the complex genetic circuits that control the cell. 

​Technological advances are having a major impact on molecular biology. Advances in experimental techniques mean that large amounts of sequence, expression, and localization data are now routinely gathered by individual investigators. In addition terabytes of these kinds of data are stored in various public and private databases. Concurrently, access to large scale computing resources has become more and more common in molecular biology laboratories. Students in the Computational and Systems Biology Program will learn to leverage these advances in both experimental and computational resources. 

Faculty in the Computational and Systems Biology Program work on a variety of different biological problems, but in most cases students will find a tight coupling between computational and experimental approaches. Some of the general areas in which faculty work include:

University of Washington, Life Sciences Building | Skanska - Global  corporate website
  • Large-scale genetic network analysis and reconstruction
  • Technology development for high-throughput collection of genetic and biochemical data  
  • Molecular modeling of genetic regulatory circuits
  • Real time, single cell analyses of genetic regulatory circuits 
  • Specificity and evolution of DNA-protein interactions 
  • Algorithm development for comparison of DNA, RNA, and protein sequences 
  • Synthetic Biology Complex trait analysis 
  • Population genetic analysis of genetic variation 
  • Functional genomic approaches to disease gene identification

The Ph.D. programs in Computational Biology at Johns Hopkins University span four Departments and a wide range of research topics. Our programs provide interdisciplinary training in computational and quantitative approaches to scientific problems that include questions in genomics, medicine, genome engineering, sequencing technology, molecular biology, genetics, and others.

Our students are actively involved in high-profile research, and have developed very widely-used bioinformatics software systems such as Bowtie, Tophat, and Cufflinks. and the more-recent systems HISAT and Stringtie (for RNA-seq alignment and assembly) and Kraken (for metagenomic sequence analysis). The work they do with Hopkins faculty prepares them to go on to postdoctoral and tenure track faculty positions at top-ranked universities including (in recent years) Harvard, MIT, the University of Washington, Carnegie Mellon, and Brown.

Students in computational biology at Hopkins can enroll in one of four different Ph.D. programs. These include Biomedical Engineering, ranked #1 in the nation; Biostatistics, ranked #5 in the nation; Biology, ranked #5 in the nation; and the rapidly growing Computer Science Department, which moved into a state-of-the-art new building, Malone Hall, in 2015.

CCB faculty have appointments in each of these programs, and some of us maintain appointments in multiple programs. To determine which program fits your interests and background, browse the course lists below. Each program has a separate application process; please apply specifically to the departments you’re interested in. (Note: this page may not be up to date, so please use the Department websites for the latest information.) Applications to multiple programs are permitted, but if you’re not certain, we encourage you to contact potential faculty advisors before you apply. Wherever you apply, make it clear that your interest is Computational Biology.

Sample Course Offerings for Ph.D. students in Computational Biology

Department of Biomedical Engineering, Whiting School of Engineering

The Johns Hopkins Department of Biomedical Engineering (BME), widely regarded as the top program of its kind in the world and ranked #1 in the nation by U.S. News, is dedicated to solving important scientific problems at the intersection of multiple disciplines and that have the potential to make a significant impact on medicine and health. At the intersection of inquiry and discovery, the department integrates biology, medicine, and engineering and draws upon the considerable strengths and talents of the Johns Hopkins Schools of Engineering and Medicine. See the BME Ph.D. program website for many details beyond the brief summary here.

Ph.D. program

The BME course requirements are very flexible, allowing Computational Biology students to craft a program designed for their interests. 36 credits (typically 10-12 courses) are required for the Ph.D., with 18 in life sciences and 18 in quantitative sciences. Quantitative sciences include engineering, computer science, applied mathematics, computational biology, and biostatistics. A Ph.D. student in computational biology might be interested in these courses:

  • 580.588 Foundations of Computational Biology and Bioinformatics II
  • 580.420 Build-a-Genome
  • 580.689 Computational Personal Genomics
  • 550.560 Statistical Models in Molecular Medicine
  • 580.423 Systems Bioengineering III (systems biology)
  • 600.639 Computational Genomics

Other courses that might be part of a Ph.D. in BME include:

  • 580.421 Systems Bioengineering I (cardiovascular)
  • 580.422 Systems Bioengineering II (neuroscience)
  • 540.409 Modeling Dynamics and Control for Chemical and Biological Systems
  • 520.610 Computational Functional Genomics
  • 520.636 Feedback Control in Biological Signaling Pathways
  • 540.659 Bioengineering in Regenerative Medicine
  • 580.639 Models of Neuron
  • 580.682 Computational Models of the Cardiac Myocyte
  • 580.690 Systems Biology of Cell Regulation
  • 140.751-756 Advanced Methods in Biostatistics

A unique feature of the Hopkins BME program is that students may also opt to take the 1st-year Medical School curriculum to satisfy most of their course requirements. Many students choose this option, in which they sit side by side with the students in Hopkins’ highly-ranked M.D. program.

Department of Computer Science, Whiting School of Engineering

Computer Science at Johns Hopkins University is a diverse, collaborative, and intensely research-focused department. In 2015, the Department moved into a brand new, state-of-the-art research building, Malone Hall, designed around the needs of students and faculty. See the video highlighting the new building and some of our students here. The faculty represent a broad spectrum of disciplines encompassing core computer science and many cross-disciplinary areas including Computational Biology and Medicine, Information Security, Machine Learning, Data Intensive Computing, Computer-Integrated Surgery, and Natural Language Processing.

Ph.D. program

A total of 8 courses are required, and a typical load is 3 courses per semester. See the CS Department website for details. Courses that might interest a computational biology student include:

  • 600.639 Computational Genomics
  • 580.689 Computational Personal Genomics
  • 600.624 Advanced Topics in Data-Intensive Computing
  • 600.676 Machine Learning: Data to Models
  • 600.640 Frontiers of Sequencing Data Analysis
  • 600.663 Pattern Matching Algorithms
  • 600.666 Information Extraction
  • 600.688 Foundations of Computational Biology and Bioinformatics II

Plus electives that might include:

  • 600.463 Analysis of Algorithms
  • 600.465 Natural Language Processing
  • 600.475 Machine Learning
  • 600.420 Parallel Programming
  • 600.615 Big Data, Small Languages, Scalable Systems
  • 600.466 Information Retrieval and Web Agents

For the Computer Science Ph.D., 2 out of the required 8 classes can be taken outside the Department. These may include any of the courses in the BME, Biostatistics, and Biology programs listed on this page.

Department of Biostatistics, Bloomberg School of Public Health

Johns Hopkins Biostatistics is the oldest department of its kind in the world and has long been considered as one of the best. It is ranked #5 in the nation by U.S. News.

Ph.D. program

At least 18 credits required outside the Dept of Biostatistics, at least 9 of these in the School of Public Health. See the Department website for details.

All students in the Biostatistics Ph.D. program have to complete the core requirements:

  • A two-year sequence on biostatistical methodology (140.751-756)
  • A two-year sequence on probability and the foundations and theory of statistical science (550.620-621, 140.673-674, 140.771-772);
  • Principles of Epidemiology (340.601)

In addition, students in computational biology might take:

Computational Biology – Molecular & Cellular Biology Graduate Program
  • 140.776.01 Statistical Computing (3 credits)
  • 140.638.01 Analysis of Biological Sequences (3 credits)
  • 140.644.01 Statistica machine learning: methods, theory, and applications (4 credits)
  • 140.688.01 Statistics for Genomics (3 credits)

Further courses might include 2-3 courses in Computer Science, BME, or Biology listed on this page.

Department of Biology, Krieger School of Arts and Sciences

The Hopkins Biology Graduate Program, founded in 1876, is the oldest Biology graduate school in the country. People like Thomas Morgan, E. B. Wilson, Edwin Conklin and Ross Harrison, were part of the initial graduate classes when the program was first founded. Hopkins is ranked #6 in the nation in Biological Sciences by U.S. News

Quantitative and computational biology are an integral part of the CMDB training program. During the first semester students attend Quantitative Biology Bootcamp, a one week intensive course in using computational tools and programming for biological data analysis. Two of our core courses – Graduate Biophysical Chemistry and Genomes and Development – each have an associated computational lab component.

Ph.D. in Cell, Molecular, Developmental Biology, and Biophysics (CMDB):

The CMDB core includes the following courses:

  • 020.607 Quantitative Biology Bootcamp
  • 020.674 Graduate Biophysical Chemistry
  • 020.686 Advanced Cell Biology
  • 020.637 Genomes and Development
  • 020.668 Advanced Molecular Biology

Electives include courses such as:

  • 020.606 Molecular Evolution
  • 020.620 Stem Cells
  • 020.630 Human Genetics
  • 020.640 Epigenetics & Chromosome Dynamics
  • 020.650 Eukaryotic Molecular Biology
  • 020.644 RNA
computational biology – Washington University School of Medicine in St.  Louis

university of washington bioinformatics masters

Master of Science in Biomedical Informatics

Degree Description:

The certificate emphasizes the acquisition of biological and computational expertise by supplementing graduate students’ existing background with necessary training in molecular biology, genomics, and computer science. There is a clear need for the development of expertise to analyze the growing amount of biological data generated from genomic, phenotypic, environmental, and other sources. The goal of the certificate is to provide the coursework and a richer academic environment for graduate student to synthesize information across multiple disciplines. The certificate is aimed to prepare highly qualified graduate students who have rigorous multidisciplinary training in molecular biology, genomics, and computer science.

The certificate is aimed at graduate students in engineering, sciences, computer science, and agriculture, although students from other colleges may also find it valuable. The primary objective is to provide students an interdisciplinary training in bioinformatics. Our goal is to develop among the students a critical scientific understanding of bioinformatics, including the biological and computational aspects of algorithm development and implementation.

Admission Requirements:

Admitted Masters or Ph.D. students under the advisement of WSU faculty, and post-graduate professionals who earned their degree in an appropriate field, are eligible to apply for the certificate program. Students who are eligible will notify their department’s graduate committee and their guidance committee of their interest in the certificate. Once the guidance committee has agreed that it is in the student’s best interest to pursue and complete the certificate, the student will apply to the Bioinformatics Certificate committee. The application will include a statement from the student’s advisor and graduate committee supporting the application. In this way, we hope to enhance the disciplinary degree.

For students to excel and get the most out of their participation in this certificate, we anticipate that students should have proficiency in the following: one year of calculus, coursework in probability and statistics (strongly advised as it is required for some courses). It is also advisable for students to have 1 year of computer programming (coursework or experience), but it is not required.

The Institute for Informatics (I2) is pleased to offer a master of science in biomedical informatics. The master’s degree program is administered through I2, and the degree is conferred through Washington University School of Medicine. 

More information about our programs can be found on the Graduate Programs in Biomedical Informatics webpage.

Master of Science

  • 36 units
  • Capstone/thesis
  • Two to five years for program completion
  • Full-time and part-time options
  • Three tracks offered:
    • Translational bioinformatics 
    • Applied clinical informatics
    • Population health

Core Courses: All Tracks

All students in this program will be expected to take the core courses listed below:

  • BMI 5302 Introduction to Biomedical Informatics I (3 units)
  • BMI 5303 Introduction to Biomedical Informatics II (3 units)
  • BMI 5304 Introduction to Biomedical Data Science I (3 units)
  • BMI 5305 Introduction to Biomedical Data Science II (3 units)
  • BMI 5200 Biomedical Informatics Journal Club (2 units)
  • CLNV 510 Ethical and Legal Issues in Clinical Research (2 units) or MSB 512 Ethics in Biostatistics and Data Science (2 units)
  • Up to 10 units of research including capstone or thesis (3 units)

Scientific Writing

Students in the MS program will be expected to demonstrate completion of a scientific writing course by the time of graduation. Students who have taken the equivalent at other institutions may be excused from this course with permission of the program director. If this requirement has not been met, students will enroll in CLNV 529. This course will not count toward the 36 units required for graduation.

  • CLNV 529 Scientific Writing and Publishing (2 units)

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Undergraduate | GW Department of Biological Sciences | Columbian College of  Arts & Sciences | The George Washington University

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