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«Fall 2015 compbio.ku.edu Lawrence, KS Directory Faculty Eric Deeds Assistant Professor deeds 4-1978 Wonpil Im Professor wonpil 4-1993 ...»

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The University of Kansas

Center for Computational Biology


Fall 2015


Lawrence, KS



Eric Deeds Assistant Professor deeds@ku.edu 4-1978

Wonpil Im Professor wonpil@ku.edu 4-1993

John Karanicolas Associate Professor johnk@ku.edu 4-8298

Christian Ray Assistant Professor jjray@ku.edu 4-3206

Joanna Slusky Assistant Professor slusky@ku.edu 4-6506 Ilya Vakser Director, Professor vakser@ku.edu 4-1057 Research Faculty Petras Kundrotas Assistant Research Professor pkundro@ku.edu 4-1962 Staff Debbie Douglass-Metsker Administrative Associate douglass@ku.edu 4-1057 David Johnson Research Engineer habib@ku.edu 4-1942 Postdoctoral Fellows Arnab Bandyopadhyay arnabrkmv@ku.edu 4-3206 Andrea Bazzoli bazzoli@ku.edu 4-1973 Madhurima Das madhurimadas@ku.edu 4-1962 Taras Dauzhenka t187d744@ku.edu 4-1962 Hui Sun Lee huisun@ku.edu 4-1966 Soohyung Park Spark94@ku.edu 4-1966 Dhilon Patel dspatel@ku.edu 4-1966 Yifei Qi yfqi@ku.edu 4-1966 2 Graduate Students Yusuf Adeshina yusuf.adeshina@ku.edu 4-1973 Ivan Anishchenko anishchenko.ivan@ku.edu 4-1962 Varsha Badal v309b752@ku.edu 4-1962 Saveliy Belkin saveliy@ku.edu 4-1962 Jimmy Budiardjo jbudi101@ku.edu 4-1973 Meghan Franklin* mwfranklin@ku.edu Pushpa Itagi pushpaitagi@ku.edu 4-1966 Nathan Jenkins* nwjenkins@ku.edu David Johnson habib@ku.edu 4-1942 Karen Khar biokhar@ku.edu 4-1973 Seonghoon Kim s236k458@ku.edu 4-1966 Chris Kropiewnicki* ck8625@gmail.com Joonseong Lee* j930l080@ku.edu Jumin Lee j712l362@ku.edu 4-1966 Jiaqin Li elainejiaqinli@ku.edu 4-4528 Shipra Malhotra shipramalhotra@live.com 4-1973 GW McElfresh* gwmcelfresh@ku.edu Sang-Jun Park* s252p488@ku.edu Ryan Suderman ryants@ku.edu 4-1199 Huijing Wang h749w664@ku.edu 4-3206 *1st Year 3


The Director of Graduate Studies is your first stop for any questions related to graduate study or requirements. Our Director of Graduate Studies is John Karanicolas. If you would like to research an issue in advance of speaking with the Director of Graduate Studies or if you still have

questions, the following document provides assistance:

clas.drupal.ku.edu/sites/clas.ku.edu/files/docs/COGA/KEY OFFICES AT KU (FINAL).pdf Program Information I. Graduate Program Progress to Degree Goal and objectives The goal of graduate education for the Ph.D. degree within the Computational Biology Program is to enhance students’ academic knowledge base, teaching ability, communication ability, and in-depth basic research ability within a particular scientific area in the discipline.

Year One The student will begin taking formal courses to fulfill requirements for the degree, including the Bioinformatics core course. At least two individual lab rotations are required for each new graduate student during the first year of graduate study. By the end of the first year the student will select the thesis Advisor. During the first and subsequent years, the student is required to attend the weekly Computational Biology seminar series. The student is also required to participate in the Computational Biology Student Seminar series.

Year Two By the end of the second year, the student will have completed the formal course work to fulfill requirements for the degree. The student will complete and submit a research proposal for the Comprehensive Oral Exam. This proposal will be written in the format of a National Institutes of Health (NIH) or National Science Foundation (NSF) grant proposal. The proposal must develop a research topic related to the general areas of computational biology. The topic of the research proposal is decided upon by the student in consultation with the thesis Advisor.

Subsequent Years Upon completion of the Comprehensive Oral Exam, the student will aggressively carry out research in the laboratory of the thesis Advisor. In addition, the student will continue attending the weekly Computational Biology seminar series and participating in the Computational Biology Student Seminar series.

A PhD degree is awarded once the student has written a final dissertation, and carried out a successful defense of it before a committee.

4 II. Policies and Procedures A. Research Laboratory Rotations for New Students Faculty Talks – All faculty members who are interested in taking a rotation student will have the opportunity to speak with new students. Faculty talks will take place the first week of classes.

Selection of Rotations – New students will contact faculty members directly to set up appointments to discuss research and possible lab rotations.

After agreeing to rotations with faculty, new students will turn in to the Director of Graduate Studies the names of the faculty members in whose labs you wish to rotate.

Each lab rotation will last approximately nine weeks, scheduled as follows:

1st Rotation 2nd Rotation 3rd Rotation 9/8/2015 – 11/6/2015 11/9/2015 – 2/5/2016 2/8/2016 – 4/22/2016 Completion of Rotations – By the end of the third rotation, submit to the Director of Graduate Studies a ranked list of faculty members with whom you would like to work.

Every effort will be made to allow you to join your first choice lab, although there must be mutual agreement between the student and faculty member. This mutual agreement will depend on your effort and performance during the rotation, the availability of continued financial support, the availability of space within the lab, and so on. If the first choice cannot be fulfilled, the second choice will be examined under the same constraints. Once a mutual agreement has been reached, new students will officially join research labs. If, after the end of the first year, a student has not identified a Major Advisor for research, the student will be dismissed from the graduate program.

In rare instances a situation may arise such that you, your advisor, or both desire a change in advisor. Before any action is taken by either party, the Director of Graduate Studies and your Graduate Committee will be apprised of the situation and discussion of the issue initiated. A resolution will be reached in a timely manner.

B. Enrollment Requirements K.U. has on-line enrollment. Check out the Graduate Studies Enrollment page at graduate.ku.edu/enrollment and follow along.

The Computational Biology Program has established a minimum credit hour level of enrollment that is appropriate for normal progress (i.e., course work and research effort) and which is representative of faculty time required for a student’s work towards an advanced degree. These requirements must equal, and may exceed the minimum credit hour enrollment limit set by Graduate Studies. Program enrollment requirements

are as follows:

1. Ph.D. Enrollment Hours: Pre-Comprehensive Oral Students who have not yet passed the Comprehensive Oral Exam are expected to enroll in at least 9 credit hours each fall and spring semester and 3 credit hours each summer session.

2. Ph.D. Enrollment Hours: 18-Hour Post-Comp Rule 5 After passing the Comprehensive Oral Exam, you must be continuously enrolled, including summer sessions, until all degree requirements are completed. According to Graduate Studies regulations, for the first 18 hours of post-comprehensive enrollment, the doctoral student must enroll in a minimum of 6 credit hours per semester and 3 credit hours per summer session.

3. Ph.D. Enrollment Hours: Beyond the 18-Hour Post-Comp Rule Students who have completed the 18-Hour Post-Comp requirement are now eligible to enroll in fewer than 6 hours per semester, as long as some of these are for dissertation credit (BINF 999). Before you do this, please see the Director of Graduate Studies to complete the necessary form.

C. Academic Performance Grading Systems - Graduate courses use the ABCDF grading system or the SU performance criteria (S = satisfactory performance and U = unsatisfactory performance). Thesis and dissertation research courses are graded with the latter.

Academic Standing - Only grades of "A" or "B" in graduate courses are considered satisfactory. If a grade of “C” or below is obtained, you will not receive graduate credit for this course and the course must be retaken. If your cumulative grade-point average falls below “B” (3.0 on a 4.0 scale), you are automatically placed on academic probation and will be required to raise your cumulative grade-point average to at least a “B” (3.0) during the next semester. If, after the second semester, a student who has probationary status fails to maintain a "B" (3.0) cumulative grade point average, the student will be dismissed from the graduate program. Grades such as “P”, “S”, “U” and “I” are omitted from these calculations. You will not be allowed to hold a GTA or GRA appointment until probationary status has been removed.

D. Graduate Assistantships

The following mechanisms are available for graduate assistantship:

Graduate Fellowship: Competitive graduate fellowships are available, including University Graduate Fellowships (graduate.ku.edu/university-graduate-fellowships) and the Madison & Lila Self Graduate Fellowship (selfgraduate.ku.edu). Applications should be coordinated with the Director of Graduate Studies.

Graduate Teaching Assistantships (GTAs): GTAs are provided on a semester-bysemester basis. Students holding these appointments must make arrangements with their Major Advisor for summer appointments. The specific GTA is set by Program requirements and expertise of the student.

Graduate Research Assistantships (GRAs): Individual faculty may have Graduate Research Assistantships (GRAs) available from grant funds. GRAs are appointed for one semester at a time.

E. Tuition and Fees If you hold a GTA slot, the University will pay your tuition plus 3 graduate credit hours of campus fees.

If you hold a GRA slot, your mentor is responsible for paying your tuition. Please be sure to consult with your mentor in advance of payment deadlines. You are also required to complete a Staff Tuition Rates Form for EVERY semester that you hold a GRA appointment.

F. Progress to Degree Forms The Progress to Degree form (PTD) enables the University to track and collect vital information about students’ progress to degree. Upon receiving the information from you, the Director of Graduate Studies will complete the necessary PTD form and forward it to Graduate Studies for approval. Thus, it is very important that you contact the Director of Graduate Studies when you do ANY of the following: change degree status, form a committee, hold a committee meeting, schedule an exam, schedule a seminar, schedule a defense, or change degree program. If you’re not sure about something, please check with the Director of Graduate Studies.

G. Seminars All graduate students will be expected to attend Center for Computational Biology seminars. These are generally speakers from outside the University, scheduled on some Tuesdays at 1:00 p.m. in the Computational Biology seminar room in MRB (unless otherwise noted).

H. University Policies and Degree Requirements For up-to-date CLAS- and University-level degree requirements, consult the official


clas.drupal.ku.edu/sites/clas.ku.edu/files/docs/COGA/UNIVERSITY POLICIES AND DEGREE REQUIREMENTS (FINAL).pdf 7 III. Curriculum A. Computational Biology Core Courses First Year Computational Biology Core Course BINF 701/702 is the Computational Biology core course developed at the KU Center for Computational Biology. The course is designed to introduce the most important and basic concepts, methods, and tools used in computational biology. Topics include (but not limited to) bioinformatics databases, sequence and structure alignment, protein structure prediction, protein folding, protein-protein interaction, Monte Carlo simulation, and molecular dynamics. Emphasis will be put on the understanding and utilization of these concepts and algorithms. The objective is to help the students to reach rapidly the frontier of computational biology and be able to use the computational tools to solve the problems on their own research. For more information about these courses please contact Wonpil Im. Email: wonpil@ku.edu.

Second Year Computational Biology Core Course BINF 703/704 is the second year core course for Compuational Biology students. It is designed to introduce students to important topics in thermodynamics and statistical physics, the emerging field of systems biology, structural biology, and protein design with a special emphasis on the use of mathematical and computational models to study biological phenomena as dynamical systems. Topics include (but are not limited to) graph theory, nonlinear systems of differential equations, stochastic simulations, rulebased methods, thermodynamics of protein structure, and protein design. In each case, we focus both on analytical approaches and numerical methods. We also discuss in detail the application of these algorithms to interesting problems in gene regulation, signaling networks, and macromolecular self-assembly. The objective is to help students develop an understanding of state-of-the-art methodologies that they can apply to problems they encounter in their own research. For more information about this course please contact Eric Deeds. Email: deeds@ku.edu.

B. Required Courses BINF 701 Computational Biology Core I (5) BINF 702 Computational Biology Core II (5) BINF 709 Topics in Bioinformatics BIOL 636 Biochemistry I (3) BIOL 638 Biochemistry II (3) BIOL 804 Issues in Scientific Integrity (1) or CHEM 700 Responsible Scholarship in Chemical Sciences(1) or MDCM 801 Issues in Scientific Integrity (1) BINF 999 Dissertation Research (1-18)

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