Overview
Quantitative approaches like spatial transcriptomics, metabolomics, cryo-electron microscopy, single-molecule imaging, and machine learning are revolutionizing our understanding of the biological systems relevant for human health. In this systems setting, successful development and use of such approaches requires cooperation amongst individuals who care deeply about biological mechanisms and bring expertise from areas like physics, chemistry, computer science, statistics, and mathematics. The Physiology, Biophysics, and Systems Biology (PBSB) graduate program is a home for such faculty and trainees. Together, we answer questions like:
“How does the three-dimensional architecture and rearrangement of the chromatin network control cellular programming?
“How are dynamics coordinated across a macromolecular assembly to mediate transmembrane signaling?"
“How is the interplay between tumor cells and the immune system regulated by the stromal environment?
“How are complex biological spatial patterns assembled with stereotyped precision?”
“How is the selectivity of molecular interactions established and what is the basis for targeted protein and drug trafficking, transport, and recognition in cells and organs”
“What are the design principles optimizing information flow in electrogenic tissue?"
To begin tackling such questions, students in the PBSB program initially emphasize their training in either of two complementary areas of quantitative biology.
Stream A focuses on how information is expressed and organized in molecular and cellular systems, drawing heavily from the fields of computer science and statistics. Coursework focuses on building expertise with the algorithms and high-throughput strategies used to understand the organization of biological information at the genetic, proteomic, cellular, and physiological systems levels. In their research, students often use and advance approaches like
- single-cell sequencing
- spatial transcriptomics
- epigenomics
- metabolomics
- multi-omic integration
- deep learning
to identify patterns in normal and pathological settings that guide mechanistic understanding, therapeutic strategy, and drug development.
Stream B focuses on how the interactions of various components in molecular and cellular systems generate and process information, relying on theoretical and experimental approaches from physics, chemistry, mathematics, and engineering. Coursework fosters an understanding of fundamental biophysical principles with wide-ranging applications to proteins, membranes, macromolecular systems, intracellular signaling pathways, and cellular network function. To uncover biophysical mechanisms underlying health and disease, students in Stream B often use and advance tools like
- single-molecule imaging
- atomic-force microscopy
- cryo-electron microscopy
- electrophysiology
- magnetic resonance imaging
- multi-photon fluorescence microscopy
- molecular dynamics simulations
- network theory and simulations
- machine learning algorithms
Together, this training in quantitatively understanding how information is organized and processed in biological systems develops scientists poised to make impactful contributions to human health.
Research and Faculty
Our students begin research within days of arriving on campus and stay heavily involved in research throughout their graduate career. In their first year, students complete a minimum of three immersive research rotations, from which students select their thesis mentors. We provide students with a wealth of resources and support during their graduate years and encourage them to take the lead in moving their project forward shortly after joining their thesis lab.
The PBSB faculty are engaged in world-class research aimed at understanding the functional mechanisms in the human body in health and disease. Program faculty have appointments in various departments, including Physiology and Biophysics, Medicine, Biochemistry, Pharmacology, Radiology, Computational Biomedicine, Neuroscience, Genetics, and Cell and Developmental Biology. Faculty are unified by a shared dedication to tackling challenging questions in biological systems through quantitative bioinformatic and biophysical approaches that lead to new understanding, new interventions, and new therapies.
We invite you to explore the profiles of our faculty and the many research topics available to our students.
Curriculum
Within living systems, numerous components interact and give rise to responses that span disparate scales. This makes biological research particularly challenging, but the curriculum of the PBSB program teaches students how to deal with this challenge through rigorous quantitative approaches and discussion-intensive courses.
All students in the program complete a common core course on how quantitative computational and theoretical tools are used to describe, understand, and test biological properties and mechanisms. All students also actively participate or present in seminar series which develop their ability to communicate science and place their newfound knowledge into context.
Students in Stream A take a second core course entitled Quantitative Information in Biological Systems that covers topics in genomics, epigenomics, proteomics, single-cell sequencing, and image analysis, and a third core course focused on genome-wide association studies. Stream A students also typically take elective coursework on the foundations of data science, high-throughput sequencing strategies, and applied machine learning.
Students in Stream B take a core course in Biophysical Principles of Molecular and Cellular Systems that covers topics in protein structure and function, thermodynamics, diffusion, signaling pathways, metabolism, DNA repair, and information transmission. Stream B students also commonly take elective coursework on biochemical and biophysical methods, foundations of data science, and dynamics models in biology.
More information about PBSB program courses is available at Courses.
Current Students and Alumni
PBSB students are a select cohort, comfortably bridging the traditionally quantitative scientific disciplines and the complex challenges of biological systems. Our students lead new areas of investigation, drive established fields towards more quantitative understanding and methods of exploration, publish in respected journals, and are highly sought after upon graduation. Alumni most often continue to careers in academic research, biotechnology, or data science. Our favorable faculty-to-student ratio (~1:1) and dedicated mentorship ensures that every student receives the guidance and advice they need to find their own path.
We invite you to explore more information on student life and the Weill Cornell Graduate School student experience.
PBSB Program at Houston Methodist
In 2021, the PBSB program expanded by founding a new program at the Houston Methodist Academic Institute. This program extends the long-standing academic affiliation between Weill-Cornell Graduate School and Houston Methodist to provide graduate training. This collaboration enhances the experience of students and faculty at both locations, promotes scientific interactions, and adds diversity to our student body.
Students and WCGS faculty at Houston Methodist engage in the WCGS curriculum via remote programming, with visits to New York City for program retreats and graduate school events, and with thesis research undertaken at Houston Methodist.
For more information, please see our website for the PhD in Physiology, Biophysics & Systems Biology at Houston Methodist.
Application
We welcome applications from any individual who values the use and development of quantitative experimental, computational, and theoretical approaches for tackling challenging biological problems of medical relevance. Applicants should have demonstrated excellence and ambition in their previous coursework. We also expect that applicants will have had at least one significant research experience.
It is recommended that, either through formal coursework, research, or independent study, all applicants will have had meaningful exposure to biochemical principles, molecular biology, introductory chemistry, introductory physics, statistics, calculus, linear algebra, and coding (Python, C, Matlab, R, or similar). In addition, it is recommended that applicants interested in Stream A have had some exposure to machine learning and those interested in Stream B to differential equations.
See Apply Online for application deadline, procedures, and requirements.
