- Morningside Graduate School of Biomedical Sciences
- Academics
- PhD Biomedical Sciences
- Biophysical, Chemical and Computational Biology Pathway
Biophysical, Chemical, and Computational Biology (BCCB) Pathway
A dedicated pathway for students with quantitative backgrounds, with no expectation of experience in biological sciences. Apply your quantitative skills at the interface of physical and biological sciences to solve pressing problems in biomedical sciences that require new and innovative approaches.
Discover the BCCB PhD pathway
In the BCCB pathway, you will:
- Develop the skills needed to apply quantitative, inter-disciplinary approaches to biomedical research
- Explore diverse research opportunities through first-year rotations
- Receive full funding, including a generous stipend and health insurance
CURRICULUM
The BCCB curriculum is designed to accelerate students transition from quantitative sciences into biomedical research, enabled by individualized academic mentorship. Coursework begins with a dedicated first-year core course focused on the application of quantitative approaches to biomedical science, which emphasizes problem solving and critical thinking. Subsequent electives provide opportunities to delve more deeply into areas of interest that prepare you for thesis research involving the application of quantitative methodology to biomedical sciences.
Additionally, enroll in professional development and qualifying exam prep courses that equip you with the practical skills of proposal writing, data management, career exploration and how to communicate effectively in writing, graphics and orally to the scientific community.
PROGRAM STRUCTURE
BCCB students are assigned an academic mentor with similar educational history. The mentor will work with the student to identify appropriate electives or tutorials to ensure their educational needs are met. This individualized plan ensures that students with diverse undergraduate backgrounds are equipped for successful thesis research. In their first-year, students enroll in the 2-semester BCCB core course: How Biophysical, Chemical and Computational Strategies Impact Biological Research. This course is taken in parallel with research rotations, providing students with the opportunity to explore the vast research opportunities. Additional courses during are available during the second and third years, which provide introduction to advanced topics, responsible conduct in research, and preparation for the qualifying exam. The program culminates in the public oral defense of the dissertation.
OUR LEADERSHIP
Celia Schiffer, PhD
Program Co-Director
Chair and Professor
email Dr. Schiffer
James Munro, PhD
Program Co-Director
Associate Professor
email Dr. Munro
OUR FACULTY
-
Nezar Abdennur
Our research focuses on how the epigenome and genome-organizing processes drive cell decision-making, and how these states and processes are disrupted in disease and aging. We develop methods to comprehensively integrate, mine, and visualize 3D genomic, functional genomic, and multi-omic data. We also lead and participate in open-source initiatives to improve legacy bioinformatics approaches and make them more accessible and interoperable with the greater data science and AI/ML ecosystem.
-
Robert Brewster
In the Brewster Lab we use concepts from physics and engineering to enable a theory-first approach to the study of gene regulation. The work in our lab blends synthetic biology approaches, designed to test the predictions of simple mechanistic theories, to reveal the fundamental rules governing gene regulation and to build a predictive understanding of the control of gene expression. Members of my lab join with a mixture of backgrounds and develop a full arsenal of pen-and-paper theory, computational and wet lab skills.
-
Yingleong (Rigel) Chan
Our group's primary research is to use population in-vitro models to the causes of human neurological diseases such as Alzheimer's and Multiple Sclerosis. We commonly use human donor stem-cell derived models as well as patient bio-samples to collect high-throughput data for testing genetic and environmental effects. We seek students who are interested in performing laboratory experiments to collect such high-throughput data and perform research to develop novel bioinformatic methods for analysis and interpretation.
-
Andres Colubri
The Colubri lab brings together computational scientists, software engineers, and visual designers to develop new methods and tools for infectious disease research. With our partners at the Broad Institute of MIT and Harvard and The Inspire Project, we have created Operation Outbreak, the world's first live, app-based outbreak simulator to generate ground-truth datasets, validate predictive models, and improve the response to future pandemics. We seek collaborations at the intersection of epidemiology, genomics, machine learning, data visualization, and mobile technologies with the goal of advancing an interdisciplinary vision of outbreak science.
-
Job Dekker
Our lab aims to understand the molecular and biophysical mechanisms that determine how chromosomes are folded inside living cells. We employ genetic, genomic, and imaging methods in combination with computational approaches and polymer physics to determine the structure, dynamics and function of chromosomes. We study chromosome folding in a range of different organisms with a focus on humans and dinoflagellates.
-
Niko Grigorieff
The Grigorieff lab visualizes cellular macromolecular assemblies in atomic detail using cryo-microscopy (cryo-EM), to better understand the mechanisms underlying their function. The lab focuses on template matching, a method to detect molecules and assemblies in situ – inside cells – for a more complete spatial understanding of their local distribution, and to preserve weak and transient interactions otherwise missed. The newly developed tools are implemented in open-source software and made available to the wider scientific community.
-
David Grunwald
Our biological research interests lay in the function of the cell nucleus, focusing on elucidating mRNA trafficking in the nucleus, its transport across the nuclear membrane, and the interplay of different transport pathways. Our approach aims at understanding the basic mechanisms of nuclear function, especially as several diseases have been directly linked to defects in mRNA nucleocytoplasmic transport. Our ambition is to reproduce the biochemical and physical reactions elucidated in the test tube directly in the cell using genetic labels for proteins and RNA combined with viral gene delivery and genome editing tools (CRISPR) to make these reactions visible using fluorescence microscopy.
-
Jason Kim
My research spanning over 30 years focuses on type 2 diabetes and obesity, and I have made a significant contribution to the field with 185 peer-reviewed publications, mostly in high-impact scientific journals, receiving more than 36,400 citations. As an internationally recognized scientist funded by the NIH since 2001, I study the molecular link between obesity and metabolic diseases using elegant physiological and molecular approaches. My current research program, supported by 2 recently awarded NIH-R01 grants from the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute on Aging with $5.5 million in total budget, investigates the molecular mechanism of metabolic liver disease and an important connection between type 2 diabetes and Alzheimer’s disease. As the liver and the brain are heterogeneous organs consisting of multiple cell types, my research involves single-cell transcriptomic (scRNA-Seq) analysis to examine transcriptional profiles in isolated hepatocytes, neurons, and immune cells (e.g., Kupffer cells, microglia) and spatial transcriptomic analysis involving multiplexed error-robust fluorescence in situ hybridization (MERFISH) to map expression and localization of inflammatory genes in liver and CNS cells. All of these analyses involve big data requiring a comprehensive bioinformatics approach with rigor for data interpretation that will be aided by knowledge and skills in biostatistics and computational biology.
-
Michael Lee
We are a laboratory of systems pharmacology. We use a combination of genetic and biochemical tools to understand how cells respond to drug perturbations. Using this information, we develop computational models of drug responses to identify and validate new ways to improve drug efficacy.
-
Li Li
I am a biochemist/computational biophysicist by training. My lab uses various chemical, biochemical, and biophysical methods to study how RNA chemical modifications regulate mRNA translation and RNA folding. Our long-term goal is to use these fundamental insights to develop more durable and potent mRNA therapeutics.
-
Teng Ting (Elaine) Lim
My research group works at the intersection of statistical genetics, quantitative genomics, genome engineering and computational methods development for studying neurological diseases using human stem cell derived models. We seek to train students with quantitative backgrounds to work with cutting-edge genomics and genetics datasets to solve molecular and biological questions related to neurological diseases.
-
Francesca Massi
The focus of my laboratory is to understand the relationship between the structure, stability, and dynamics of proteins. In particular we investigate how the structure and dynamics of a protein affect molecular recognition, binding specificity, allostery and stability. To this end, we take a multi-disciplinary approach combining the strengths of biophysical, biochemical and in vivo techniques, with particular emphasis on solution NMR spectroscopic and computational methods.
-
Stephen Miller
Our lab uses chemistry and light to study biology. We design and construct bioluminescent and fluorescent probes that emit beyond the visible wavelength region, in the near infrared, where tissue is most transparent to light. Our interests range from basic research into the evolution and molecular basis for the light-emitting chemistry of bioluminescence to the practical application of optical probes to report on gene expression and enzymatic activity in mouse models of disease.
-
Amir Mitchell
Our primary areas of interests are antibiotic resistance, bacterial colonization of cancer tumors, and interactions within microbial communities. Our experimental work leverages on genomics, transcriptomics, and quantitative high-throughput microscopy and is complemented by computational analysis and mathematical modeling. We aim to increase the throughput of genetic screening and functional genomics by leveraging on robotic automation, big-data analysis, and machine learning.
-
James Munro
The Munro laboratory studies how the structural dynamics of macromolecules are coupled to their function. We are focused primarily on viral proteins and seek to determine how their dynamics evolve in response to immune pressure and inter-species transmission. To this end, we develop and apply fluorescence-based biophysical approaches at single-molecule resolution.
-
Mary Munson
The Munson lab uses a combination of biochemical, biophysical and structural techniques to elucidate the molecular mechanisms that underlie membrane trafficking in eukaryotic cells. These include studies of protein-protein and protein-lipid interactions, conformational changes, and structures of the exocyst complex and its binding partners, who control exocytosis, and VPS45 and its partners, who function in the endosomal pathway.
-
Athma Pai
Our lab lies at the intersection of RNA biology, computational genomics, and systems biology. Our central goal is to understand the dynamic nature of gene regulation in eukaryotic systems, focusing on studying the speed and efficiency at which RNA molecules are created and processed to ensure proper cellular functions. To do so, we combine high-dimensional quantitative analyses with novel functional genomics approaches to address both fundamental mechanistic questions and computationally predict cellular responses across changing environmental contexts.
-
Oliver Rando
The Rando lab studies epigenetic inheritance in a variety of species. We employ a broad range of genomic tools, often designing or adopting sophisticated computational methods to extract biological insights from "big data." In addition, we are currently keenly interested in the organization of the genome in mature sperm, a problem that we hope to address using chemical, biophysical and even structural approaches.
-
Nick Rhind
As a failed mathematician, I still have a fondness for quantitative and computation approaches to biology; be it the formal logics of cellular genetics, modeling of DNA replication kinetics or analysis of size-dependent protein expression dynamics. The DNA replication kinetics work in the lab relies heavily on automated image analysis and stochastic modeling. The cell size control work uses protein-expression modeling to try to understand how a cell could tell how big it is.
-
Sean Ryder
We wish to understand how information is transferred from one generation to the next through molecules in the cytoplasm. Specifically, we study how maternal mRNAs are produced, stored, and activated at precise moments to coordinate early embryonic decisions. Our work blends quantitative biochemistry and biophysics with cutting edge molecular genetics tools to study RNA regulation from molecules to phenotype.
-
Manoj Saranathan
I am an MRI physicist with wide interests in MR physics, pulse sequence development, image reconstruction, and image processing and their applications to neuro and body imaging. My current research interests are focused on ultra high-resolution imaging and segmentation of deep brain structures like thalamus and claustrum and the specificity of their involvement in pathology such as frontotemporal dementia, multiple sclerosis, Alzheimer's disease, and schizophrenia Another area of interest is high spatio-temporal resolution dynamic contrast enhanced MRI for quantification of renal function and breast/prostate cancer.
-
Celia Schiffer
Our laboratory uses experimental and computational structural biology and chemistry to predict the molecular basis for drug resistance and develop strategies for developing more robust (resistance-avoiding) therapeutics. Our research program focuses on viral proteases (HIV, HCV, HTLV-1, ZIKV, Dengue, Enteroviral and SARS-CoV2), viral entry mechanisms and innate immune response enzymes including APOBEC3s. The techniques we use range from protein crystallography, CryoET to protein engineering and enzyme inhibition to molecular dynamics and machine learning.
-
Elizabeth Shank
The Shank lab studies microbial interactions. We combine traditional microscopy and molecular genetics with analytical chemistry, mass spectrometry, fluorescence imaging, and microfluidics to tackle questions about how bacteria chemically, metabolically, and spatially interact. By integrating large-scale experimental approaches with quantitative analyses, we aim to gain insights into microbial ecology to improve both human and environmental health.
-
Kuang Shen
The mTORC1 pathway is a central regulator for cell growth and proliferation. It controls general cellular metabolic reactions, and its malfunction usually leads to severe consequences in human health. The Shen lab utilizes single molecule FRET, cryo-EM, and enzyme kinetics to characterize the nutrient sensing pathway in cells, and we aim to provide a quantitative framework of how mTORC1 pathway functions in cells.
-
Jie Song
Using a combination of synthetic chemistry and bioengineering tools, my lab designs functional biomaterial scaffolds (e.g. biodegradable shape memory polymers, viscoelastic hydrogels with predictive and widely tunable degradative properties) to guide skeletal tissue regeneration. These biomaterials are also tailored for the controlled encapsulation and delivery of cell, protein and lipid therapeutics. We also develop novel implant coatings to combat periprosthetic infections.
-
Larry Stern
Our research group studies the molecular mechanisms that underlie immune system recognition, with an emphasis on MHC proteins, T cell receptors, and antigen processing and presentation pathways. We use techniques from structural biology, mechanistic enzymology, computational biology, and big-data ‘omics approaches to address questions in human immunology and mouse models. Our overall goal is to understand how the immune system recognizes and responds to pathogens and cancer, and how this system is dysregulated in autoimmune disease.
-
Marian Walhout
In the Walhout lab we aim to understand how biological networks are organized, how their organization enables function, and how these networks evolve. We use a variety of experimental and computational systems biology approaches to map and characterize gene regulatory networks and to understand how regulatory circuitry controls animal development, function, and homeostasis. Ultimately, we aim to understand how dysfunctional networks affect or cause diseases like diabetes, obesity and cancer.
-
Lingfei Wang
Lingfei obtained his Ph.D. in theoretical physics and now seeks to reverse engineer causation from data in high-dimensional systems. He develops novel algorithms and statistical methods to infer and analyze causal gene regulatory networks. This covers a wide range of topics in theoretical physics, machine learning, population genetics, and single-cell and spatial multi-omic data.
-
Jonathan Watts
The Watts lab works at the interface of chemistry, biology and pharmacology in the development of platform technologies for oligonucleotide therapeutics (gene silencing, gene activation and gene editing). Our work is centered in the design and synthesis of modified and multimeric oligonucleotides and their testing in cell and animal models of disease. The modifications we design enable higher activity, improved specificity, longer duration of effect, and better bioavailability in multiple tissues relative to current technologies.
-
Zhiping Weng
Our research integrates genomics, epigenomics, transcriptomics, and molecular recognition to decipher gene regulation, focusing on computational analysis of large datasets. We elucidate the role of regulatory elements in human diseases and explore genetic variations' impact on gene regulation and disease susceptibility. Additionally, we investigate the biogenesis and function of small silencing RNAs, especially PIWI-interacting RNAs, through advanced computational methodologies.
-
Eviatar Yemini
The Yemini Lab combines computational methods with experimental neurobiology. We employ state-of-the-art AI/ML and computer-vision algorithms to decipher the link between neural communication and animal behaviors. Lab members regularly design and build advanced hardware and software to image neural activity, in living animals, using cutting-edge microscopes and microfluidic devices.
-
Qing Yu
The proteotype, encompassing the complete interactive ensemble of proteins expressed by an organism or in a single cell, is the crucial bridge connecting genetic information (genotype) to observable characteristics (phenotype). However, our understanding of the proteotype remains significantly limited, due to the extreme complexity and a lack of tools. Pioneering technology innovation in proteomics, our multidisciplinary team is dedicated to unraveling the complexities of the proteotype in both health and disease. We delve into the dynamic world of proteins to decipher their roles in cellular signaling and aim to systematically elucidate the molecular mechanisms underlying various physiological and pathological processes (e.g., aging, cancer). Our mission extends beyond mere exploration, as we strive to leverage these insights to catalyze advancements in drug discovery.
-
Phillip Zamore
The Zamore lab seeks to understand the biology and mechanism of paradigmatic examples of Argonaute proteins and pathways, and, ultimately, to use these insights to design and improve small RNA-guided therapies for human diseases.
-
Jin Zhang
We are interested in the interplay between sensory systems and internal physiology. For example, taste is largely impacted by our internal state (e.g., food tastes better when we are hungry); conversely, taste stimulation triggers downstream physiological responses, and long-term taste experience shapes behavior. Using multidisciplinary approaches such as single-cell sequencing, live animal calcium imaging, and animal behavior, we aim to understand how the nervous system integrates external and internal information to drive behavior and maintain homeostasis.