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NLM Training Program in Biomedical Informatics
Curriculum and Research Experience
The GCC / Keck Center member institutions provide a uniquely rich teaching environment, including a diverse set of courses in biosciences, biomedical sciences, computer science, health informatics, and mathematics that are directly appropriate for the NLMTP. With six institutions involved in the GCC, the array of possible courses to meet these requirements is impressive. The NLM Training Program will serve the needs of a young physician who wishes to expand her analytical and computational knowledge, a biologist who wants to develop expertise in functional genomics, or a computer scientist who wants to prepare himself for a research career in computational biology. Consequently, we have a competency-based curriculum where the specific courses and other training experiences offered to the trainees must meet their particular needs and mesh with the academic programs of their departments.
As we have done in the past, the NLM Training Program Steering Committee will oversee course selection by all NLM training program predoctoral students and may extend or expand a normal departmental curriculum. We believe that this oversight, which requires some extra work to forge coherent training across departments, institutions and particular trainee interests and backgrounds, has proved its worth in the training record of the Keck Center. Key to this process is a long-standing inter-institutional agreement on cross-registration for courses between participating Keck Center institutions. Graduate students can receive credit for courses taken at any other of the institutions. This arrangement, coupled with the close proximity of the institutions and two-way videoconferencing between our institutions, removes the usual barriers to inter-institutional curriculum design. This agreement is a further testament to the ability of the partner institutions to work together to leverage strengths in a collective program.
Since trainees are admitted to the program following their first year of study, which is generally the most intensive year of coursework, their time during their training period will be heavily oriented to their research project. However, the trainees are also required to pursue coursework in the area complementary to their primary field of study (i.e., biological scientists must take courses in computer and mathematical sciences, and vice versa). Each student receives advising and specific suggestions about coursework appropriate to their background and research interests during their annual progress review. A variety of courses are available, including those developed for this program as well as those extant at each of the institutions.
Key to this structure is a long-standing inter-institutional agreement on cross-registration for courses without fees between our institutions. Graduate students at any of the participating institutions can enroll in and receive credit for courses taken at any other of the institutions without the necessity for tuition remuneration. This arrangement, coupled with the close proximity of the institutions removes the usual barriers.
In addition to the didactic courses that are required by their home departments and by the Keck Center, the trainees are required to attend the weekly Keck Seminar, engage in NLM trainee discussions, attend the spring and fall retreat/symposia, and attend other special activities that may be scheduled (e.g., seminars by distinguished speakers supported by the GCC/Keck Center, journal clubs in their area of interest, etc.).
In general, most of the pre-doctoral trainees will spend more than 50% of their time in their second and third years of study in research, and in their later years of study this level will approach 80%.
NLM Training Program predoctoral students must also meet the requirements of their GCC home departments regarding coursework, oral or written candidacy exams, research progress reviews, thesis defense and publication. Thus, an NLM trainee may take on extra coursework and will certainly commit to more presentations and rigorous review procedures beyond those assumed by a regular departmental predoctoral student. The result, however, is that NLM trainees will be anchored in traditional disciplines with enhanced career opportunities.
The Core of the Curriculum
NLM trainees, in addition to fulfilling the course requirements of his or her home department, will take more advanced courses in one or more of the domains relevant to their research interests. They are required to take a minimum of three courses in their non-primary discipline, plus must attend the weekly Keck seminar in which all Keck Center trainees participate, and must present a poster at selected research conferences. Required attendance at the annual NLM Training Program Conference helps to link the trainees to the broader informatics community.
The Training Committee will work with trainees and mentors to determine what additional work will be required to meet competency goals in other domains in light of the trainee’s past and current academic work and present research goals. A trainee, for example, may enter the program with clear competence in one of the foundations of the curriculum: biomedicine, computation or statistics and mathematics. In such a case, the Training Committee may grant credit for previous work or may require some course work to broaden the trainee’s knowledge in the domain. The Training Committee will determine which courses at the participating institutions satisfy the three domain requirements. For example, a statistics course at MDACC and one at Rice may be sufficiently comparable for one to substitute for another in the NLM training program curriculum.
The Role of Research and Curricular Electives in the Curriculum
Elective courses will be used to strengthen a trainee’s preparation for research. The GCC institutions offer a great many courses that are potentially relevant to predoctoral study in biomedical informatics. In the NLM Training Program, we emphasize areas in which the Keck Center institutions and participating faculty have considerable expertise. Our program focuses on the research domains of informatics, multi-dimensional and functional imaging, and simulation of macromolecular and cellular behavior.
The trainee’s mentor will be principally responsible for creating the opportunities for research experience and training in the broad areas indicated in the previous section. The curriculum focuses on fundamental disciplinary expertise for our trainees, whereas the research program provides a setting in which to apply this knowledge — both to discover where information is lacking and to deepen understanding, develop intuition, and expand experience. The research element of pre- and (even more importantly) post-doctoral training is the critical component in engendering a career-long understanding of how to approach a question, to formulate a strategy, and find the pathways that effectively address the manifold issues that emerge in answering the question. Our faculty mentors are therefore crucial in this training process, working with students on a daily basis to guide them as they develop their own method and style of problem-solving. Trainees receive their degrees from their home department; and an increasing number of degrees will result from dual mentoring of students by faculty in those departments and those in the research areas discussed above.
Supervised Research Experience
Each trainee must complete an independent, supervised research program as part of their training, both to fulfill their departmental requirements and those of the training program. The NLM training faculty have been selected for their demonstrated skills and interest in guiding pre- and postdoctoral training. These faculty members are actively involved in our teaching programs and committed to the joint educational activities of the NLM program, including cross-institutional courses, joint seminar series, symposia, workshops, and annual retreats. Most importantly, these scientists and engineers have extensive experience in directing Ph.D. students and postdoctoral fellows in research, leading to extensive publications, high-quality dissertations, and the realization of successful research careers. As a group, the NLM faculty has successfully trained hundreds of Ph.D. students and postdoctoral trainees.
Faculty mentors have been chosen from throughout our six institutions to represent the fields necessary for the effective development and deployment of new computational tools in modern biology and biomedicine. The subject areas encompass the intellectual framework needed to ask incisive biological questions, develop appropriate algorithms to approach the problems, and to execute the methods on modern computational architectures. On this basis, each faculty member can be grouped into at least one, and often more, of the thrust areas of this training program — imaging, informatics, and simulation/modeling.
Here we provide an overview of the research areas that trainees may pursue, noting again that the participating GCC departments provide many combinations of courses—and the Keck Center has great expertise—by which trainees can gain knowledge and skill for their research endeavors in these areas. In our description of these areas, the list of mentors indicates the interconnectedness of the Keck faculty. Note that these are also the research areas and mentors open to our postdoctoral trainees. Following these descriptions, we also illustrate curriculum management with two examples from our current NLM program.
The research/training groups involved in the Keck Center are at the forefront of their respective areas, and these laboratories are outstanding settings for the proposed training program. The research interests of the faculty can be grouped conveniently into three focus areas, although significant interactions occur both within and across these groups.
- Informatics
- Multidimensional and Functional Imaging
- Simulations of Macromolecular and Cellular Behavior
Detail on the research activities of the training faculty in each of these areas follow:
a. Informatics
The area of Informatics covers a wide range of fields comprising bioinformatics, computational biomedical sciences (including biostatistics), and health informatics. Through the Keck Center and the Gulf Coast Consortium for Bioinformatics, NLM trainees have access to vast research and training opportunities in this general arena. For example, opportunities exist to focus on genomics, proteomics, drug and macromolecular design, genetic and molecular bases of diseases, as well as patterns of gene expression in individuals and populations. Interdisciplinary as well as inter-institutional research groups address key computational issues such as annotation, assembly, sequence alignment, manipulation of massive databases, the analysis of expression data and functional assignment.
The Keck Center has a strong cadre of applied mathematicians, statisticians and computer scientists who bring a wealth of expertise to the Informatics focus. A few specific mathematical, statistical and computational approaches pertinent to this vast arena of interdisciplinary activity and areas of active research among Keck scientists are evolutionary trees; branching and Markov processes; general stochastic processes and stochastic simulation; Bayesian modeling; high dimensional data reduction methods, including principal component analysis, clustering, pattern recognition, feature extraction; error estimation; the general area of artificial intelligence; constraint satisfaction, which includes the area of non-linear programming; query optimization on large databases; and graphical representation of complex data and complex structures.
Health Informatics faculty in the School of Health Information Sciences (SHIS) at UTHSC-H provide informatics research and training opportunities for students in clinical application areas. Extensive Health Informatics coursework is also available in the SHIS. Faculty research interests include modeling of complex human problem-solving in healthcare, the representations of knowledge for automating these processes, and the application of cognitive science and decision science to the understanding and improvement of human-computer interaction in clinical environments. Clinical domains of application being investigated are quite diverse and encompass the extensive computerized medical systems in the outpatient and inpatient facilities at Hermann Memorial and Methodist Healthcare systems and the flight surgeon discipline related consoles at the Mission Control Center at NASA/JSC and medical informatics capability on board the International Space Station.
b. Multidimensional and Functional Imaging
In the post-genomic era, one of the challenges in biology is to understand dynamic behavior and function in biological systems at all levels — from molecules and macromolecular machine to organelles, cells, tissues and organs — a range that spans over six orders of magnitude in scale. The spatial and temporal relationships of multiple components at each level, and their dynamic interactions are key for answering fundamental questions in both normal and abnormal biological processes. Direct visualization is often the only way to comprehend the intricate interplay in such complex systems. The cutting edge approaches in structural biology encompass mapping the fold space of proteins via structural genomics analyses and moving beyond individual components in isolation or even small assemblies of components in simplified in-vitro systems. Understanding spatial and temporal relationships between molecules in the cellular context is critical to improvements in drug design and to our understanding of dynamic processes in living systems. "Pictures" facilitate our understanding and capture the imagination. Hence Multidimensional and Functional Imaging is a central focus of the Keck Center Biological image analysis of the future must efficiently deal with multi-dimensional images of objects of increasing complexity and detail, including the time domain. To train the next generation of students to meet these challenges will require novel approaches conceived through a well-coordinated and highly focused effort among biologists, applied mathematicians and computer scientists.
The Imaging group in the Keck Center is unique in many ways. First, we have a broad and well-balanced representation of expertise that includes x-ray crystallography, NMR spectroscopy, electron cryomicroscopy, cellular, tissue and organ imaging, applied mathematics, and computational science. Second, the faculty and students form a well-integrated and collaborative group that can solve not only routine but also exceptionally challenging computational problems for determining structures of large biological assemblies with fundamental biological significance. Third, we have an unusual instrumentation infrastructure including intermediate voltage electron cryomicroscopes, synchrotron radiation beamline access, and high field NMR spectroscopy. Many of these facilities are either national or regional facilities led by Keck Centerfaculty. Fourth, the structural biology community actively collaborates not only with local and internationally known biologists but also with computational scientists to develop novel computational tools for new paradigms in solving structures at multiple dimensions quickly, easily, and accurately.
c. Simulations of Macromolecular and Cellular Behavior
Integral to our understanding and manipulation of biosystems is the ability to predict their behavior. Simulations from the atomic level to the organismal provide information that can be utilized to design "real" experiments, to gain insight into functional properties, and to predict the outcome of specific alterations. From design of drugs or proteins with specific properties to developing insight into systemic behavior using an effective model, Simulations are essential to the modern arsenal of the bioscientific and biomedical communities. Problems of significant biological and biochemical importance are approached via careful selection of problems and using algorithm and software development targeted for scalable and metacomputing environments. Multidisciplinary interactions between investigators and students to explore the boundary between the biological sciences and the computational science community are essential for effective simulation of biological processes. The Keck Center provides a rich environment for this effort.
Curriculum Management
The Training Committee will conduct periodic reviews of its approved courses and consider the development of new ones. An example of such an innovation, which came about because of the current NLM training program, is Computational Mathematics for Biomedical Scientists. With the participation of faculty from four GCC institutions, this course introduces students to the basic tools of computational biology. The Training Committee gives particular attention to new courses to serve the needs of the Keck training programs. A representative list of courses relevant to the NLM Compuational Biology and Medicine Training Program can be found towards the end of this page.
Postdoctoral Training
The NLM postdoctoral training program differs from the predoctoral program in that there are fewer specific requirements. The goal at this level is to provide a setting for effectively maturing junior scientists into polished experts. As indicated previously, postdoctoral trainees are held to high standards of interdisciplinary research, have dual mentors, attend Keck Center seminars, and participate in the workshops, symposia, and annual retreats. These trainees also are encouraged to attend scientific meetings in their areas of interest and to present their work, and they are encouraged to give presentations at GCC/Keck Center symposia/workshops each year.
Representative Examples Of Courses Relevant To NLM Computational Biology and Medicine Training Program:
Below are examples of courses available to NLM trainees:
ADVANCED STRUCTURAL AND COMPUTATIONAL BIOPHYSICS:
MACROMOLECULAR IMAGING (taught odd years only) (311-410), BCM (3 cr. hr.)
This course is designed to discuss in-depth theoretical and practical techniques in structural biophysics with a particular emphasis on electron imaging and crystallography. Computer homework will be required. This course will serve students working in structural biophysics laboratories and will provide a comprehensive base knowledge.
ADVANCED TOPICS IN STRUCTURAL AND COMPUTATIONAL BIOLOGY (311-430), BCM (1 cr. hr.)
The course consists of student presentation of research papers from the literature and critical discussion by the class. Exposes students to faculty and senior graduate students.
BIOSTATISTICS, STATISTICAL GENETICS AND BIOINFORMATICS (STAT 453/553), RU (3 cr. hr.)
Exploration of new methods in biostatistics, statistical genetics, and bioinformatics.
COMPUTATIONAL BIOLOGY (BIOS 533) RU (2 cr. hr.)
An introduction to the emerging field of bioinformatics. A series of lectures, combined with hands-on exercises will introduce the student to various biologically relevant databases, methods to effectively search the databases, and an overall view of the various aspects of computation biology. The topics to be discussed include sequence comparison, structure analysis, phylogenetics, database searching, microarrays and proteomics.
COMPUTATIONAL MATHEMATICS FOR BIOMEDICAL SCIENTISTS (311-401)
BCM (2 cr. hr.)
Introduction to essential computational and mathematical concepts for students who are interested in computational biology and bioinformatics. It is intended that each of the concepts will be taught in the context of the real biological problems ranging from genomics to structural biophysics.
COMPUTATIONAL METHODS IN MOLECULAR BIOLOGY (310-450J) BCM (2 cr. hr.)
Provides a background in the theory and application of standard computational methods for molecular biology research. The topics to be discussed include genetic linkage analysis, sequence comparison, phylogeny, and pattern inference and matching. The course will also address computational issues for the Human Genome Program in the areas of large-scale DNA sequencing, chromosome mapping, and gene recognition.
INTRODUCTION TO STATISTICS FOR THE BIOSCIENCES (STAT 305), RU (3 cr. hr.)
Introduction to statistical models and data analysis techniques. Includes an exploration of computer-assisted data analysis with biological examples. [The development and sustaining support for this course has come directly from Keck Center participation.]
LABORATORY MODULE IN NMR SPECTROSCOPY AND MOLECULAR MODELING (BIOS 530), RU (2 cr. hr.)
Students will learn to set up, acquire, and process 1-D and basic 2-D NMR experiments. Spectral interpretation (resonance assignment and extraction of structural information) for nucleic acids and proteins, using homonuclear and heteronuclear data, will be performed. Molecular modeling, using NMR-derived structural information, will also be included. Provides an overview of the utility of NMR spectroscopy as it relates to the structure and dynamics of biologically relevant macromolecules.
LABORATORY MODULE IN SPECTROSCOPY/KINETICS (BIOS 532), RU (2 cr. hr.)
Students will learn the principles behind fluorescence, circular dichroism, analytical ultracentrifugation, spectroscopy, and rapid kinetics by carrying out experiments with genetically engineered proteins and state-of-the-art equipment. Data will be interpreted and manipulated using curve-fitting and graphics software.
PROBABILITY IN BIOINFORMATICS AND GENETICS (STAT 423), RU (3 cr. hr.) Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. This course also describes some of the main statistical applications in the field, including gene finding and evolutionary inference. [This course was developed in part by support from the NLM BISTI supplement.]
SEMINAR IN COMPUTATIONAL BIOLOGY (BIOS 592), RU (1 cr. hr.)
A discussion of selected research topics in computational biology by visitors and Keck Center participants. [Required course each semester for all NLM trainees.]
STATISTICAL GENETICS (STAT 670), RU (3 cr. hr.)
This course centers on applications of statistics in genetic problems, especially as they pertain to genotype-phenotype association. Various data structures will be the centerpiece of the course, including genotype, allele-sharing, and gene-expression. Topics include family and population-based study design, linkage, association, differential gene expression. Genetic analysis software will also be discussed and used. [This course was developed by support from the NLM BISTI supplement.]
STRUCTURAL BASIS OF HUMAN DISEASE (310-423), BCM (1 cr. hr.)
This course is designed to give students an understanding of the potential use of structural information for solving disease problems and an awareness of the different structural and computational tools. Each one-hour lecture will be taught jointly by two or more instructors who present the medical problems and the structural approaches towards solving them. [Developed for the Keck Center students.]
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