Graduate School of Medical Sciences

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Physiology, Biophysics and Systems Biology

ACE Tutorial

Review of PBSB program requirements and procedures for passing the Admission to Candidacy Exam (ACE). Principles of ACE topic choice and how to write a "winning" grant application that proposes to test a valid hypothesis will be discussed.

Advanced Topics in Cardiac Electrophysiology

This course surveys current areas of scientific interest in cardiac electrophysiology. Material covered in this course includes: introduction to cardiac electrophysiology (ion channels, action potentials, basics of cardiac electrophysiology), basic and clinical aspects of cardiac arrhythmia, dynamics, initiation, maintenance, termination of arrhythmia, arterial and ventricular fibrillation and defibrillation, experimental methods and mathematical modeling. The course is comprised of lectures as well as moderated videotaped presentations recorded recently by international experts in the field.

Bioengineering Topics

The objective of this one semester course is to prepare students for thesis research in fields that involve concepts of bioengineering, including tissue engineering and regenerative medicine. The course will be team taught by Weill Cornell and Ithaca faculty using video conferencing facilities. Examples will be chosen from musculoskeletal and cardiovascular fields.

Bioinformatics and Computational Biomedicine

This course begins with a discussion of the history, techniques and statistical analyses used in bioinformatics today. Students will begin to analyze how these tools can be used to predict RNA, gene and protein structure. The final two weeks of the course will be focused on systems biology including current techniques used to model of protein-protein interactions, protein networks and cell signaling.

Clinical and Research Genomics

The rapid advancement of Next-Generation Sequencing (NGS) has opened a wealth of opportunities for research in many fields: cancer biology, epigenetics, tumor evolution, microbiome and infectious disease dynamics, neuro-degeneration, personalized medicine, and improved diagnosis and risk assessment for patients. Moreover, there are emerging, faster NGS technologies that promise comprehensive molecular portraits of disease and actionable clinical results for doctors within a single day. Scientists and physicians will be better equipped to design studies and help patients if they possess an intricate knowledge of these molecular-profiling methods, their biological context and their applicability to specific cases and diseases. Finally, a rich understanding of the complexity of the human genome is essential for the proper annotation of characterization of any new mutations/modifications found, since large-scale efforts at tumor and normal genome sequencing have dramatically altered our view of the “normal” genome and epigenome.

Thus, in this 10-week course, students will build a strong foundation of knowledge of NGS technologies (both existing and emerging), learn the applications of these technologies for basic and clinical research, and finally learn the essential tools for the analysis, integration, and application of these data relative to other public databases and phenotype repositories. We have a broad range of expertise being contributed from many leaders in the field.

Contemporary PBSB: Cells, systems, and quantitative methods

Students prepare for 21st century research in the function, analysis, modeling and understanding of living systems at each of several scales, from the molecular through the cellular to the organ system and organism. Multiscale and translational examples develop conceptual skills necessary to design meaningful experiments, derive insight from journal reports, work within the group structure now essential for contemporary research, and communicate new developments and related findings to today’s peers and future students. Structural and developmental concepts are covered as they illuminate function. The course is modular, presented in six independent but coordinated modules. All first-year students in the PBSB Program take all six modules. The entire course and individual modules are open to students of other programs with the permission of the course director. NOTE: all students must register separately for each module taken. Each module consists of multiple weeks. Typical weeks for modules 1-5 include two in-depth lecture-conferences that combine careful presentation of core material with student participation, and conclude with either a computational analysis and/or model, or a relevant illuminating article from the literature. The final module, CPBSB6, introduces new instructional modalities and perspectives designed to instill skills essential for researchers.

Critical Dissection of Scientific Data

This course is required for all first and second year PBSB graduate students, but is open to all WCGS students. It is designed to train students in scientific presentation and critique. The structure is a formalized "journal club." Each student will choose a paper, which is subject to approval by the course directors. Each session will consist of a student formally presenting their selected paper to the class, which is expected to serve as a critical audience. The presentation should consist of an introduction of the relevant background literature, an objective presentation of the study, a subjective analysis/critique of the work and suggestions for future work. Presentations by 2nd year students will be scheduled first, giving the 1st year students the opportunity to learn from their more senior colleagues. Grading will be based on presentation quality and contribution to constructive feedback.

Faculty Research Lunches

This course is required for all first year PBSB graduate students, but is open to all WCGS students. Come for lunch and listen to program faculty describe their research.

Introduction to Bioengineering

The objective of this one semester course is to prepare students for thesis research in fields that encompass bioengineering. The course will be team taught by Weill Cornell and Ithaca faculty using video conferencing facilities. Examples will be chosen from musculoskeletal and cardiovascular fields.

Mathematical Structures in Neuroscience

This course introduces the tools of computational and theoretical neuroscience, with a focus on principles and mathematical foundations. Students should be familiar with complex numbers, matrices, and univariate differential and integral calculus. The specific topics addressed in the course vary depending on interests of the students.

Molecular Mechanisms of Membrane transport

This course focuses on the biophysics, properties, and physiological roles of ion channels and transporter. We discuss the contributions to cell function in physiology and pathology of the principal ion channel and transporter families. We emphasize the mechanistic insights that have emerged from the recent explosion of structural information and how this has drastically changed our understanding of gating and selectivity of these proteins.

Physiologic Genomics of the Cardiovascular System

A journal club and discussion seminar approach will be used to study the process of gene regulation of cardiovascular organogenesis and function. The course will focus on fundamental advances in our knowledge in genomics and how genes regulate the structure, organization and activity of the heart and vasculature. Weekly sessions will address topics that range from molecular to cellular to tissue to organ to organismal events.

Physiology, Biophysics & Systems Biology Seminar Series

This course is the seminar series in the Physiology, Biophysics & Systems Biology Program. Most lectures are given by speakers invited from outside the Weill Cornell community, but speakers are also drawn from within the Program and scientists at the WCGS with related interests.

Principles of Magnetic Resonance Imaging

After a brief overview of all major medical modalities, including x-ray, CT, MRI, SPECT/PET and US, this course will focus on the formulations of spatial encoding and image contrasts as exemplified in MRI. The inverse problem between detected signal and image source will be discussed for biomedical applications. The concepts of image resolution, image contrast, SNR and scan time will be illustrated quantitatively from an engineering point of view.

Principles of Medical Imaging

This survey course will cover the basic physical, biochemical, computational and engineering principles underlying current medical imaging techniques including: magnetic resonance imaging, positron emission tomography, radionuclide production and radiochemistry, optical imaging, X-ray computed tomography and ultrasound. The goal of the course will be to provide students with a broad knowledge of the concepts and implementation strategies of various imaging methods relevant in current research and clinical practice. Practical applications will be used to illustrate the main themes of the course. Tours of the Biomedical Imaging Core Facility and other imaging laboratories will augment the formal course material. At the end of the course students will be able to identify appropriate imaging strategies for clinical research and have a working knowledge of the major techniques available to the investigator.

Quantitative Genomics and Genetics

(Class will be taught from Ithaca - to WCMC via video-conference)

A rigorous treatment of analysis techniques used to understand complex genetic systems, this course will cover both the fundamentals and advances in statistical methodology used to identify genetic loci responsible for disease, agriculturally relevant and evolutionarily important phenotypes. Data focus will be genome-wide data collected for association, inbred and pedigree experimental designs. Analysis techniques will focus on the central importance of generalized linear models in quantitative genomics with an emphasis on both frequentist and Bayesian computational approaches to inference.

Quantitative Understanding in Biology

This course will prepare students to apply quantitative techniques to the analysis of experimental data and the modeling of biological systems. To emphasize both practical and theoretical skills, the material will be presented whenever possible in a hands-on workshop style, and the completion of several projects by the students will be required. Topics include: practical aspects of data formatting and management; communication of quantitative concepts (verbal, graphical and mathematical); a review of statistics, with emphasis on the selection of appropriate statistical tests; the use of modern software packages; the interpretation of results; the formulation, evaluation and analysis of mathematical models of biological function, with an emphasis on linear and non-linear regression, determination of model parameters; and the critical comparison of alternative models with regard to over-parameterization. The formal components will introduce (and demystify) ordinary and partial differential equations and basic principles of non-linear dynamics, in order to enable quantitative modeling in biological arenas such as neural function, enzyme kinetics, cardiac dynamics and signaling pathways. Additional special topics will also be presented (e.g., control theory, machine learning, information theory, and image analysis) and their application will be illustrated with ongoing research in the laboratories of PBSB faculty.

Responsible Conduct of Research

The objectives of this course are to: heighten students' awareness of ethical considerations relevant to the conduct of research; inform students of federal, state and institutional policies, regulations and procedures; and provide students with critical analysis and problem solving skills for ethical decision-making.

Responsible Conduct of Research

The objectives of this course are to: heighten students' awareness of ethical considerations relevant to the conduct of research; inform students of federal, state and institutional policies, regulations and procedures; and provide students with critical analysis and problem solving skills for ethical decision-making.

Scientific Computing in Biomedicine

This course will teach students the fundamental skills and knowledge required for scientific computing in the biomedical sciences. Topics include: scripting, working with large datasets, data and software management, and effective use of high-performance computing resources. Students will learn relevant theory as well as develop practical application skills using contemporary tools and technologies including R for data analysis and presentation, SQL databases for structured data management, the Ruby scripting language for practical programming tasks, git for software and data revision control, Sun Grid Engine for batch job management on large clusters, and Maestro from the Schrödinger Suite for molecular modeling and visualization.

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Weill Cornell Medicine
Graduate School of Medical Sciences
1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-5981