PREDOCTORAL TRAINING IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY

Release Date:  August 19, 1999

PA NUMBER:  PAR-99-146

National Institute of General Medical Sciences

PURPOSE

The purpose of this program announcement is to announce the establishment of a
new institutional predoctoral training grant program in the area of
Bioinformatics and Computational Biology.  The aim of this new training grant
program is to train a cadre of scientists whose primary identification and
disciplinary affiliation is in these areas.

HEALTHY PEOPLE 2000

The Public Health Service (PHS) is committed to achieving the health promotion
and disease prevention objectives of "Healthy People 2000," a PHS led national
activity for setting priority areas.  This Program Announcement, "Predoctoral
Training in Bioinformatics and Computational Biology" is related to one or
more of the priority areas.  Potential applicants may obtain a copy of
"Healthy People 2000" at http://www.crisny.org/health/us/health7.html.

ELIGIBILITY REQUIREMENTS

Applications may be submitted by domestic public and private institutions with
established programs leading to the Ph.D. degree.

MECHANISM OF SUPPORT

The mechanism of support for this program announcement is the National
Research Service Award (NRSA) institutional training grant (T32).  The current
stipend level for predoctoral trainees is $14,688 per annum.  In addition, the
applicant institution may request up to $1,500 per year for each predoctoral
trainee for essential direct support costs (including fees and health
insurance) to the training program and $300 per year for each trainee for
travel.  Tuition support for each trainee should be requested in accordance
with amounts charged to other graduate students, regardless of the source of
support, and will be paid according to the NIH tuition policy as published in
the NIH Guide for Grants and Contracts, Vol. 25, No. 2, February 2, 1996. 
Indirect costs will be paid at eight percent of total allowable direct costs
less tuition, fees, and health insurance.  Institutional training grants are
awarded for project periods of up to five years and are renewable. 
Predoctoral students may receive up to five years of support under the NRSA
provisions. However, the normal period of support on NIGMS institutional
predoctoral training grants is between one and  three years. More detail on
the policies governing the institutional predoctoral training grant awards and
further information regarding application dates, notification, tenure, trainee
eligibility, and other provisions may be found on the NIH home page at
https://grants.nih.gov/training/extramural.htm, as well as in the NIH Guide
for Grants and Contracts, Vol. 26, No. 16, May 16, 1997. Awards will be
administered in accordance with the NIH Grants Policy Statement (10/1/98),
https://grants.nih.gov/grants/policy/nihgps/, and interim updates.

RESEARCH TRAINING OBJECTIVES

Background

A workshop held on November 12, 1998,
(http://www.nih.gov/nigms/news/meetings/training.html) to evaluate NIGMS-
funded training programs identified bioinformatics and computational biology
as research areas for which inadequate training programs exist.  A follow-up
meeting, also sponsored by NIGMS, was held on March 22, 1999 to formulate
specific recommendations for training in these areas.  This program
announcement reflects the recommendations ensuing from those meetings.

The primary recommendation was to develop a mechanism to train a cadre of
scientists whose primary professional identification and disciplinary
affiliation is bioinformatics or computational biology.  The need for such a
program is a consequence of the explosion of biological data from experimental
sources coupled to the maturation of computational capabilities for large
scale analysis.  For the purpose of this announcement, bioinformatics and
computational biology are defined broadly to include the use of theory,
computer implementation and application to the full spectrum of basic research
in the biomedical sciences.  The terms thus include analysis of molecular
sequence and structure, molecular function, cellular function, physiology,
genomics, and genetics, as well as computational modeling of complex phenomena
such as neural circuits and equilibrium phenomena, population biology,
theoretical and mathematical biology, and the analysis of complex systems. 
The goal of this new program is to train Ph.D. students in the background
theory, computational implementation and biological application of information
sciences (including computer science, statistics, mathematics and others), and
to use this training to study problems relevant to biomedical research.  Of
particular interest, in light of emerging sources of biological data, are
multi-scale (different levels of abstraction) and large-scale (data intensive)
problems in biology.  The aim is to train a new class of scientist with  a
primary identity as a computational biologist/bioinformaticist, and whose
disciplinary core draws from an emerging set of principles of how to compute,
analyze and apply biological data. Thus, a successful training program in
Bioinformatics and Computational Biology will involve faculty members from a
spectrum of departments-from biologically oriented departments such as
departments of biology, biochemistry, cell biology, developmental biology,
genetics, etc., to computationally oriented departments such as departments of
computer science, engineering, statistics, mathematics, etc.

This new training grant program will become the eighth (excluding the Medical
scientist Training Program) in the series of NIGMS institutional predoctoral
training grant programs begun 25 years ago. These training grants are intended
to support the development of comprehensive multidisciplinary training
programs. They generally involve several departments and/or interdisciplinary
programs, and typically provide support for students in the early years of
graduate education.. The NIGMS training grant programs are described in more
detail on the NIGMS WWW site (http://www.nih.gov/nigms/funding/trngmech.html)

Although not a formal sponsor of this program announcement, the National
Institute of Mental Health (NIMH) is interested in fostering the training of a
new generation of neuroscientists who will bring tools and techniques from
other disciplines to apply to research questions which bear direct relevance
to mental health and mental illness.  Specifically, the NIMH seeks to support
Institutional as well as Individual Predoctoral and Postdoctoral training
opportunities in Computational Neuroscience and Neuroinformatics. Applicants
interested in pursuing training opportunities in Computational Neuroscience or
Neuroinformatics are encouraged to visit either
http://www.nimh.nih.gov/grants/rtcd.htm or
http://www.nimh.nih.gov/neuroinformatics/index.cfm. They may also contact 
Walter L. Goldschmidts, Ph.D., NIMH, at 301-443-3563 or Email: 
[email protected].

In addition, the National Human Genome Research Institute may provide funding
for portions of training grants in bioinformatics aligned with its mission.

Implementation

Applications for a training grant in Bioinformatics and Computational Biology
should address the challenges of melding two disparate cultures, computing and
biology, at both the faculty and student levels.  These challenges include:

o  Creation of a collaborative infrastructure:  Evidence for this
infrastructure could include co-authored publications, collaborative research
projects, joint service on dissertation committees, team teaching of courses,
regular interactions in journal clubs and seminar series.

o  Training of graduate students from diverse scientific backgrounds:  The
proposal should address at least two scenarios for student success, involving
students coming either from a biological background (with strong quantitative
skills) or from a bioinformatics/computational science background.

o  Degree requirements:  A successful training program should have a plan for
tailoring the requirements in Bioinformatics/Computational Biology training to
avoid extending the time to degree.  Since it is not acceptable for a program
to simply require a full set of courses and other activities in both the
biological sciences and in computer science, it is crucial that applicants
identify the key contributing ideas and skills from these two areas and remove
less relevant requirements.

o  Institutional commitment:  The application should have statements from the
appropriate Administrators and/or Deans outlining how the proposed
bioinformatics and computational biology predoctoral training program fits
within the broader vision of the institution with respect to faculty and
course development in this area, the creation of intellectual centers that
bridge these areas, and the integration of undergraduate, graduate and post-
doctoral training in the institution.

It is recognized that individual institutions will be positioned to respond in
different ways to the opportunities presented by this new training program. 
However, in addition to the  programmatic aspects addressed above, it is
important for successful applicants to address the following features:

o  Applicant pool:  It will be important to identify and recruit applications
from students with strong quantitative skills from biological backgrounds and
students from computational backgrounds with an interest in biological problem
solving.

o Rotations and/or internships: A major goal of this new training effort is to
have quantitatively trained scientists who are conversant in both experimental
biology as well as theoretical biology, computational implementation and
application of new methodologies.  Students should be exposed to the realities
of daily life in these very different research environments.  One way to
accomplish this objective is through research rotations in which students with
a predominantly biological background rotate in quantitative/computer science
laboratories and conversely, in which students with predominantly
computational training rotate in biology laboratories.  Rotations are widely
recognized as effective means to introduce students to the broadest choice of
potential thesis laboratories and cultures.  Another way to accomplish this
objective could be through internships to expose students to the
"complementary" field.  Opportunities for such internships within an academic
or industrial setting may vary between institutions.

o  Emphasis on problem solving:  Independent scientists in the area of
bioinformatics and computational biology need to be able to bring together
knowledge from disparate domains to solve important problems.  Problem-based
learning should be seriously considered in the design of a core curriculum.

o  Courses:  Courses should expose student trainees to the basic concepts in
computational biology and bioinformatics.  Both biological and computer
science courses should be included although the needs of each student will
vary depending on his/her undergraduate education.  It is incumbent on the
applicant to define a set of core concepts that graduating students will
master, even if their research projects are highly specialized.  Such courses
might include basic concepts in molecular biology, genetics, computer
algorithms and databases, especially with respect to algorithms developed in
computational biology and bioinformatics.

o  Joint mentorship: One way to enhance balanced training in both the
biological and computational sciences is to arrange for dual mentorship. In
addition, some institutions may not yet have a critical mass of faculty
members who identify themselves as a member of the field of bioinformatics or
computational biology. Arrangements for joint mentorship of students in these
fields should be considered to address the goals of this training program.

o  Student interactions:  It is clearly critical to have forums in which
predoctoral and other students in bioinformatics and computational biology can
interact, be exposed to visiting scholars and develop an internal sense of the
identity of their field-including its primary open challenges, and problems
for which satisfactory solutions exist.  Mechanisms for fostering student
interactions may include seminar series with presentations from both students,
faculty and outside speakers, retreats and journal clubs.

o  Monitoring Students:  Students should be closely monitored throughout their
graduate careers with close attention paid to time to degree and retention in
the program.

o  Involving industry in creative ways: Industry provides significant research
opportunities for bioinformatics and computational biology professionals.
Industrial affiliate programs should be considered that offer an opportunity
to further enhance the training of students through internships and other
activities that provide exposure to industrial research and development.

o  Academic and career advising: Such advice will be an important factor in
the success of these training programs since they will be creating the first
generation of students trained explicitly in computational biology and
bioinformatics.  The special considerations involved in deciding between
careers in industry and academia should be explicitly discussed.  Development
of skills for obtaining research funding also should be addressed.

o  Teaching skills: It is important to specifically encourage training of
bioinformatics and computational biology students in methods of teaching and
pedagogy.  The current shortage of a well-trained workforce in these areas
means that trainees may have significant teaching responsibilities when they
assume faculty positions at academic institutions.

It is recognized that for many institutions it may be advantageous to combine
training in bioinformatics and computational biology with training in other
areas historically supported by NIGMS institutional predoctoral training
grants.  These areas are described on the NIGMS WWW site
(http://www.nih.gov/nigms/funding/trngmech.html), and the procedures for applying  for such
combined programs are detailed in the NIH Guide for Grants and Contracts Vol.
26, No. 4, February 7, 1997.  Competitive supplements also are encouraged for
institutions that wish to expand an already funded NIGMS predoctoral training
grant to include a bioinformatics/computational biology component. Such
supplemental requests should identify a distinct pool of applicants with good
quantitative skills, and new training activities and opportunities that
address the goals of this program announcement.

APPLICATION PROCEDURES

Applicants must use the grant application form PHS 398 (rev. 4/98).  The kit
contains special instructions for Institutional National Research Service
Awards (T32).  Application kits are available at most institutional offices of
sponsored research and from the Division of Extramural Outreach and
Information Resources, National Institutes of Health, 6701 Rockledge Drive,
MSC 7910, Bethesda, MD 20892-7910, telephone (301) 710-0267, Email: 
[email protected].  Application kits are also available on the Internet at:
https://grants.nih.gov/grants/forms.htm

In addition, the review will be facilitated if the applicants organize the
required information in a consistent format.  Suggestions are given on the
NIGMS WWW site (http://www.nih.gov/nigms/funding/nrsatablesintro.html)

The title and number of the program announcement must be typed on line 2 of
the face page of the application form and the YES box must be marked.

Submit a signed, typewritten original of the application, including the
Checklist, and five signed, photocopies, in one package to:

CENTER FOR SCIENTIFIC REVIEW
NATIONAL INSTITUTES OF HEALTH
6701 ROCKLEDGE DRIVE, ROOM 1040 - MSC 7710
BETHESDA, MD  20892-7710
BETHESDA, MD  20817 (for express/courier service)

REVIEW CONSIDERATIONS

Applications that are complete will be reviewed for scientific and technical
merit by an appropriate peer review group convened by the NIGMS in accordance
with NIH peer review procedures and criteria for T32 applications.  All
applications judged to be competitive during the initial merit review will be
discussed, assigned a priority score and receive a second level by the NIGMS
Advisory Council.

Review Criteria

Items considered in the review of applications for NIGMS Institutional
Predoctoral National Research Service Awards include:

Program Direction:

o  Origin and development of the program
o  Research and training leadership and experience of the program director
o  Adequacy of the program administration and advisory structure

Participating faculty members

o  Composition of the faculty (by rank and distribution in different fields
and departments); mechanisms and criteria for inclusion
o  Current independent research grant support (competitive, national)
o  Publication records
o  Nature and breadth of research conducted in areas pertinent to this program
announcement
o  Evidence of collaboration and cooperation among faculty members
o  Experience in the supervision of research training

Training Program

o  Goals of the program and rationale for program organization
o  Mechanisms and criteria for the recruitment and selection of trainees
o  Mechanisms to monitor and guide the trainees
o  Nature and extent of research opportunities, courses, and seminars in areas
pertinent to this program announcement
o  Provisions/activities to promote cohesiveness of the program
o  Opportunities for collaborative research
o  Integration of computational and biological science training
o  Flexibility for trainees to take courses, rotations and mentorships in any
of the involved departments or programs.

Trainees and Candidates for Training

o  Availability of qualified candidates (backgrounds, academic credentials)
o  Caliber of current and/or potential trainees and others identified with the
program Publication records of past and current trainees

Research and Training Environment

o  Institutional support for the training program
o  Other sources of training support available
o  Facilities and resources available to the program
o  Numbers of predoctoral and postdoctoral students affiliated with
participating laboratories

Special Considerations (items evaluated by the review committee but not
included in the assignment of a priority score)

o  Efforts and achievements in recruitment of underrepresented minority
students to the program
o  Training in responsible conduct of research

AWARD CRITERIA

Applications will compete for available funds with all other recommended
applications.  The following will be considered in making funding decisions:

o  Quality of the proposed training program as determined by peer review
o  Availability of funds
o  Program priority

INQUIRIES

Inquiries are strongly encouraged.  The opportunity to clarify any issues or
questions from potential applicants is welcome.

Direct inquiries regarding programmatic issues to:

James C. Cassatt, Ph.D.
Division of Cell Biology and Biophysics
National Institute of General Medical Sciences
Building 45, Room 2AS19
Bethesda, MD  20892
Telephone:  (301) 594-0828
FAX:  (301) 402-2004
Email:  [email protected]

Marion M. Zatz, Ph.D.
Division of Genetics and Developmental Biology
National Institute of General Medical Sciences
Building 45, Room 2AS25
Telephone:  (301) 594-0943
FAX: (301) 480-2228
Email:  [email protected]

Inquiries regarding supplements to existing training grants should be directed
to the program administrator of the existing grant.

Direct inquiries regarding fiscal matters to:

Ms. Carol Tippery
Grants Management Office
National Institute of General Medical Sciences
45 Center Drive, MSC 6200
Bethesda, MD  20892-6200
Telephone:  (301) 594-5135
FAX:  (301) 480-1969
Email: [email protected]

AUTHORITY AND REGULATIONS

This program is described in the Catalog of Federal Domestic Assistance No.
93.821, 93.859, 93.862.  Awards are made under authorization of the Public
Health Service Act, Title IV, Part A (Public Law 78-410, as amended by Public
Law 99-158, 42 USC 241 and 285) and administered under the NIH Grants Policy
Statement (10-1-98) and Federal Regulations 42 CFR 52 and 45 CFR Part 74. 
This program is not subject to the intergovernmental review requirements of
Executive Order 12372 or Health Systems Agency review.

The Public Health Service (PHS) strongly encourages all award recipients to
provide a smoke-free workplace and promote the non-use of all tobacco
products.  In addition, Public Law 103-227, the Pro-Children Act of 1994,
prohibits smoking in certain facilities (or in some cases, any portion of a
facility) in which regular or routine education, library, day care, health
care or early childhood development services are provided to children.  This
is consistent with the PHS mission to protect and advance the physical and
mental health of the American people.

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