CSHL’s research faculty has a rich history of contributing some of the most fundamental discoveries in molecular biology and genetics. This legacy, which includes 8 Nobel Prize winners, continues to be strengthened today by the 50 faculty members who head cutting-edge laboratories in a broad range of fields, some of which are often and increasingly interdisciplinary. Their efforts and output are consistently, internationally recognized. Thomson Reuters’ Essential Science Indicators, a leading index for institutional performance, has ranked CSHL in the top 1% of institutions most cited in published research and its faculty among the top three in terms of its influence in molecular biology and genetics.
neuronal circuits, sensory coding and synaptic plasticity, neuronal correlates of behavior, olfactory processing
How does the brain encode stimuli from the outside world to give rise to perceptions? What does a smell look like in the brain? The focus of my group is to understand how neural circuits compute sensory-motor transformations across different contexts, senses, and brain states to generate meaningful behaviors.
sleep, neuromodulators, cancer neuroscience, homeostasis, host-tumor physiology
Patients with cancer frequently experience debilitating symptoms that can impair quality of life and reduce odds of survival. These include drastic changes in appetite, sleep/wake cycles, cognitive function, and pain, among others. Our lab aims to uncover mechanistic interactions between the brain and cancer that drive these phenomena. Reciprocally, we investigate how manipulation of specific brain circuits influences cancer processes in the body.
ovarian cancer, breast cancer, genetics, genomics, genetic susceptibility, early natural history
My research interests are in the molecular genetics, genetics, and genomics of gynecologic and breast cancers. Currently I am focused on the early natural histories of ovarian carcinoma and metastatic breast cancer, the genomics of ovarian cancer stem/progenitor cells, and the hypothesis that most breast cancers result from polygenic susceptibility.
Animals are faced with many decisions. They must integrate information from a variety of sources – sensory inputs like smell and sound as well as memories and innate impulses – to arrive at a single behavioral output. My laboratory investigates the neural circuits that underlie decision-making.
computational genomics, transcriptomics, epigenomics, gene regulation, big data, precision medicine
Next generation sequencing technologies revolutionized many areas of genetics and molecular biology, enabling quantitative analyses of the entire genomes and paving the way for Personalized Medicine. We develop novel statistical methods and computational algorithms for multi-omics processing and integration, and leverage Big Genomic Data to elucidate various problems in precision health, such as genetic and epigenetic mechanisms of cancer development and progression, and clinical impact of functional variants.
Among the changes that occur during pregnancy, those affecting the breasts have been found to subsequently modify breast cancer risk. My laboratory investigates how the signals present during pregnancy permanently alter the way gene expression is controlled and how these changes affect normal and malignant mammary development.
Ph.D., University of Copenhagen and the Danish Cancer Society, 2000
tumor microenvironment, intravital imaging, tumor-associated myeloid cells, neutrophil extracellular traps, breast and pancreatic cancer
Cancer cells are surrounded by immune cells, blood vessels, chemical signals and a support matrix—collectively, the tumor microenvironment. Most microenvironments help tumors grow and metastasize, but some can restrict tumors. My lab studies how to target the bad microenvironments and support the good ones to combat cancer.
Ph.D., Humboldt University of Berlin, Germany, 2007
neural dynamics and computation, neural circuit models, machine learning, stochastic processes, dynamical systems theory, decision-making, attention
My lab investigates how perception and cognition arise from changes in neural activity. We develop and apply computational methods to discover dynamic patterns in large-scale neural activity recordings. We then create mathematical models to explain how these activity changes emerge from signaling between neurons, ultimately driving behavior.
M.D., Johns Hopkins University School of Medicine, 1968
cancer immunology, pancreatic cancer, mouse models
I’m studying how to harness the power of the immune system to fight cancer. Our underlying premise is that the microenvironment within a tumor suppresses the immune system. We have found a way to eliminate this suppression in the mouse model of pancreatic cancer, which has led to development of a drug for human pancreatic cancer that will enter phase 1 clinical trials in 2015.
The nervous system transmits information by passing chemical signals from one nerve cell to the others. This signal transmission relies on a variety of proteins to receive and transmit the chemical signals. My group studies the structure and function of neurotransmitter receptors and ion channels that regulate fundamental neuronal activities.
co-expression, meta-analysis, single cell expression, gene networks, multifunctionality
Of the tens of thousands of protein-coding genes in the human genome, only a small portion have an experimentally defined function. For the rest, how can we determine what they do? My lab develops computational predictions based on co-expression networks. We are applying our predictions to understand neuropsychiatric disorders.
genome-wide organization of transcription and the functional roles of non-protein coding RNAs
Only a small portion of the RNAs encoded in any genome are used to make proteins. My lab investigates what these noncoding RNAs (ncRNAs) do within and outside of cells, where regulators of their expression are located in the genome, and how perturbations of ncRNAs and their regulators contribute to disease.
post-transcriptional gene regulation, control of animal developmental timing, RNA biology
As organisms develop, genes turn on and off with a precise order and timing, much like the order and duration of notes in a song. My group uses model organisms to understand the molecules that control the tempo of development. We also study how changes in the timing of gene expression contribute to diseases like cancer.
To ensure that cells function normally, tens of thousands of genes must be turned on or off together. To do this, regulatory molecules - transcription factors and non-coding RNAs – simultaneously control hundreds of genes. My group studies how the resulting gene networks function and how they can be compromised in human disease.
Professor Charles Robertson Professor of Neuroscience
Ph.D., Brandeis University, 1994
development and function of the GABAergic inhibitory circuitry in neocortex, cortical circuits, mouse genetics, developmental plasticity, neurogenomics, autism
Studies the development and organization of neural circuits in the mouse cerebral cortex. His team uses an integrated approach to identify neuronal cell types and discover how they interact to process information and guide behavior, focusing on the motor cortex that controls forelimb movement. His studies of inhibitory interneurons, such as chandelier cells, have implications for understanding schizophrenia and autism.
computational biology, molecular networks, human genetics, human disease, applied statistical and machine learning, biomedical text-mining, molecular evolution
Every gene has a job to do, but genes rarely act alone. Biologists have built models of molecular interaction networks that represent the complex relationships between thousands of different genes. I am using computational approaches to help define these relationships, work that is helping us to understand the causes of common diseases including autism, bipolar disorder, and cancer.
plant development, stem cell signaling, genomics and imaging
My lab studies genes and signals in cells that regulate the growth and shape of plants. We have discovered several genes that control plant architecture by exerting an influence on stem cells. By identifying the genes that control the number of stem cells in corn plants, for example, we’ve discovered a means of boosting the yield of that vital staple.
host response to cancer, metabolism, immunology, cancer immunotherapy, cachexia, physiology of patients with cancer
Cancer is a systemic disease. Using both laboratory and clinical research, my group investigates the connections between metabolism, endocrinology, and immunology to discover how the body’s response to a tumor can be used to improve treatment for patients with cancer.
Our cells depend on thousands of proteins and nucleic acids that function as tiny machines: molecules that build, fold, cut, destroy, and transport all of the molecules essential for life. My group is discovering how these molecular machines work, looking at interactions between individual atoms to understand how they activate gene expression, DNA replication, and small RNA biology.
From regulating gene expression to fighting off pathogens, biology uses DNA sequence information in many different ways. My research combines theory, computation, and experiment in an effort to better understand the quantitative relationships between DNA sequence and biological function. Much of my work is devoted to developing new methods in statistics and machine learning.
sequence-function relationships, deep learning, representation learning
Deep learning has the potential to make a significant impact in biology and healthcare, but a major challenge is understanding the reasons behind their predictions. My research develops methods to interpret this powerful class of black box models, with a goal of elucidating data-driven insights into the underlying mechanisms of sequence-function relationships.
The complexity of the mammalian brain challenges our ability to explain it. My group applies methods from mathematics and theoretical physics to understand the brain. We are generating novel ideas about neural computation and brain development, including how neurons process information, how brain networks assemble during development, and how brain architecture evolved to facilitate its function.
posttranscriptional control of gene expression, alternative splicing, splicing in genetic diseases and cancer, splicing-targeted antisense therapeutics
Our DNA carries the instructions to manufacture all the molecules needed by a cell. After each gene is copied from DNA into RNA, the RNA message is "spliced" - an editing process involving precise cutting and pasting. I am interested in how splicing normally works, how it is altered in genetic diseases and cancer, and how we can correct these defects for therapy.
in silico genomics of cancer, single-cell genomics, early detection of cancer, inference from noisy biological data
Many types of cancer display bewildering intra-tumor heterogeneity on a cellular and molecular level, with aggressive malignant cell populations found alongside normal tissue and infiltrating immune cells. I am developing mathematical and statistical tools to disentangle tumor cell population structure, enabling an earlier and more accurate diagnosis of the disease and better-informed clinical decisions.
single-cell, in situ RNA-seq, non-coding RNA, spatial genomics, cancer microenvironment, pancreatic cancer
Cells are amazingly complex, with the ability to sense, and remember timing, location and history. I am exploring how cells store this information, and how their surroundings influence their communication with other cells. I am also developing various imaging and molecular sequencing methods for tracking genes, molecules, and cells to understand how cancer cells arise and evolve.
computational biology, human genetics, phylogenetics, copy number variation
We have recently come to appreciate that many unrelated diseases, such as autism, congenital heart disease and cancer, are derived from rare and unique mutations, many of which are not inherited but instead occur spontaneously. I am generating algorithms to analyze massive datasets comprising thousands of affected families to identify disease-causing mutations.
synapse, physiology and plasticity, neural circuits, fear processing, reward processing, rodent behaviors related to mental disorders
My group studies the neural circuits underlying cognitive function and dysfunction as they relate to anxiety, depression, schizophrenia and autism. We use sophisticated technologies to manipulate specific neural circuits in the rodent brain to determine their role in behavior. We are interested in changes in synaptic strength that may underlie mental disorders.
Professor & HHMI Investigator Jacob Goldfield Professor of Genetics
Ph.D., Watson School of Biological Sciences at Cold Spring Harbor Laboratory, 2004
plant developmental genetics, mechanisms of phase transitions for flowering time and inflorescence branching, heterosis
My research team studies the genes that determine when and where, and thus how many, flowers are produced on plants. Flowers form on branches called inflorescences, which originate from stem cells. By studying the genes that control how stem cells become inflorescences, we are able to manipulate flower production to improve crop yields.
cancer, metastasis, metabolism, nutrition, cellular signal transduction, redox, homeostasis, epigenetics
Tumor growth depends upon cancer cells acquiring nutrients from their environment and using these molecules to fuel proliferation. My group studies the nature and regulation of metabolic adaptation during tumorigenesis and metastasis, with the intention of identifying metabolic vulnerabilities that can be targeted for cancer therapy.
Professor & HHMI Investigator William J. Matheson Professor
Ph.D., Cambridge University, 1986
plant genetics, transposons, development, gene regulation, DNA methylation
Chromosomes are covered with chemical modifications that help control gene expression. I study this secondary genetic code - the epigenome - and how it is guided by small mobile RNAs in plants and fission yeast. Our discoveries impact plant breeding and human health, and we use this and other genomic information to improve aquatic plants as a source of bioenergy.
computational biology, sequence-function relationships, population genetics, protein evolution, machine learning
Some mutations are harmful but others are benign. How can we predict the effects of mutations, both singly and in combination? Using data from experiments that simultaneously measure the effects of thousands of mutations, I develop computational tools to predict the functional impact of mutations in protein coding sequences.
genomics of psychiatric disorders, genomics of cancer, computational genomics, plant genomics
Over the last two decades, revolutionary improvements in DNA sequencing technology have made it faster, more accurate, and much cheaper. We are now able to sequence up to 10 trillion DNA letters in just one month. I harness these technological advancements to assemble genomes for a variety of organisms and probe the genetic basis of neurological disorders, including autism and schizophrenia, better understand cancer progression and understand the complex structures of the genomes of higher plants.
Cells employ stringent controls to ensure that genes are turned on and off at the correct time and place. Accurate gene expression relies on several levels of regulation, including how DNA and its associated molecules are packed together. I study the diseases arising from defects in these control systems, such as aging and cancer.
A theoretical physicist by training, my research is centered around intelligent machines. I do both theoretical and experimental work. The theoretical work is focussed on analyzing distributed/networked algorithms in the context of control theory and machine learning, using tools from statistical physics. My lab is involved in brain-wide mesoscale circuit mapping in the Mouse as well as in the Marmoset. An organizing idea behind my research is that there may be common underlying mathematical principles that constrain evolved biological systems and human-engineered systems.
algorithms in nature, biological computation, neural circuits, plant architectures
Biological systems must solve problems to survive, and their solutions can be viewed as “algorithms.” Our goal is to uncover these algorithms, translate them to improve computer science, and use them to spark new hypotheses about biological function and dysfunction.
M.D., Medical School of Charles University, Prague, 1991
Ph.D., SUNY Downstate Brooklyn, 1995
neurobiology of autism and schizophrenia, gene expression-based mapping of brain activity, anatomical mapping of brain connectivity, high throughput microscopy
To understand what’s going wrong in illnesses like autism and schizophrenia, we need to know more about how neural circuits are connected in the healthy brain. We’ve developed advanced imaging methods to draw the first whole-brain activation map in the mouse. Now we’re applying that technology to study changes in brain activity in mice whose behavior models human autism and schizophrenia.
Unlike animals, plants neither have specific organs that see or hear various stimuli, yet, plants are sensitive to their surrounding environment and modify their development according to various external signals. My lab studies how the environment of a plant modulates its growth and development. Understanding environmental control of growth will have far-reaching implications for agriculture, energy production, and many other human activities.
olfaction, audition, communication behaviors, in vivo electrophysiology, individual recognition
When confronted with another individual, social animals use multiple sensory inputs smells, sounds, sights, tastes, touches to choose an appropriate behavioral response. My group studies how specific brain circuits support these natural communication behaviors and how disruptions in these circuits can lead to inappropriate use of social information, as in Autism Spectrum Disorders.
computational biology, population genetics, computational genomics, molecular evolution, gene regulation
I am a computer scientist who is fascinated by the challenge of making sense of vast quantities of genetic data. My research group focuses in particular on questions involving human evolution and transcriptional regulation.
The immense amount of DNA, RNA and proteins that contribute to our genetic programs are precisely organized inside the cell's nucleus. My group studies how nuclear organization impacts gene regulation, and how misregulation of non-coding RNAs contributes to human diseases such as cancer.
President and Chief Executive Officer Oliver R. Grace Professor
Ph.D., Australian National University, 1979
cancer, cell cycle, DNA replication, chromatin assembly, biochemistry, yeast genetics
Every time a cell divides, it must accurately copy its DNA. With 3 billion “letters” in the human genome, this is no small task. My studies reveal the many steps and molecular actors involved, as well as how errors in DNA replication are involved in diseases that range from cancer to rare genetic disorders.
transcriptional regulation, chromatin, critical periods in neurodevelopment, steroid hormones and behavior
I am interested in how transient events during development program neurons to take on a specific identity and function. More specifically, I am studying how estrogen and testosterone generate sex differences in the brain and behavior.
Professor Caryl Boies Professor of Cancer Research
Ph.D., University of Dundee, 1985
posttranslational modification, phosphorylation, phosphatases, signal transduction, protein structure and function
Cells must constantly react to what is happening around them, adapting to changes in neighboring cells or the environment. I study the signals that cells use to exchange information with their surroundings. Our group is finding drugs that target these signals and thus can treat diabetes, obesity, cancer, and autism spectrum disorders.
cancer modeling and treatment, senescence and tumor progression, cancer visualization, PTEN regulation
We have recently developed the first genetic mouse model for therapy and analysis of metastatic prostate cancer. Now we can test if and how modern concepts of cancer evolution can outperform the 80-year-old standard of care - hormone deprivation therapy - and turn lethal prostate cancer into a curable disease.
Professor Roy J. Zuckerberg Professor of Cancer Research
M.D., Ph.D., Johns Hopkins University, 1994
pancreatic cancer, experimental therapeutics, diagnostics, mouse models, cancer genetics
Pancreatic cancer is an extremely lethal malignancy. On average, patients who are diagnosed with pancreatic cancer succumb to the disease within 6 months. Research is the only way to defeat pancreatic cancer. My lab is making progress toward finding a cure by detecting the disease earlier and designing novel therapeutic approaches.
chromatin, transcriptional regulation, acute myeloid leukemia, BET bromodomains, lysine methyltransferases
Cancer cells achieve their pathogenicity by changing which genes are on and off. To maintain these changes in gene expression, cancer cells rely on proteins that interact with DNA or modify chromatin. My group investigates how such factors sustain the aberrant capabilities of cancer cells, thereby identifying new therapeutic targets.
Professor Harold and Florence & Ethel McNeill Professor of Cancer Research
Ph.D., Catholic University of Leuven, 1991
signal transduction, Ras and Rho proteins, tumorigenesis, neuronal development and disorders
Normal cell function relies on coordinated communication between all the different parts of the cell. These communication signals control what a cell does, what shape it takes, and how it interacts with other cells. I study these signaling networks to understand how they guard against cancer and neurological disorders.
When we think of evolution, we often think about physical changes, like a plant developing broader leaves to collect more solar energy. Such evolution actually occurs within the plant’s DNA. I am using computational analysis and modeling to visualize how plant genomes have evolved over time, particularly those of staple crops. We are learning from this work to improve the range and yield of modern plants.
Professor Russell and Janet Doubleday Professor of Cancer Research
Ph.D., Columbia University, 1978
human genetic disorders, population genetics, cancer genomics
Devastating diseases like cancer and autism can be caused by spontaneous changes to our DNA—mutations first appearing in the child, or in our tissues as we age. We are developing methods to discover these changes in individuals, tumors, and even single cells, to promote early detection and treatments
My lab studies how circuitry in the brain gives rise to complex behaviors, one of nature’s great mysteries. We study how the auditory cortex processes sound, and how this is interrupted in autism. We also seek to obtain a wiring diagram of the mouse brain at the resolution of individual neurons. Our unusual approach exploits cheap and rapid “next-gen” gene sequencing technology.
Are you really what you eat? Our goal is to uncover the precise mechanisms that link nutrition to organismal health and disease states at the cellular and molecular level. A particular focus in our lab is to understand how dietary perturbations affect the immune system and contribute to the risk of diseases that are associated with immune dysfunction such as cancer.
spatial transcriptomics, immunology, central tolerance, bioinformatics
A properly functioning immune system must be able to recognize foreign invaders among the multitude of cells in the body. This ability is essential to both fight infection and prevent autoimmune diseases. We study how a specific type of immune cells, known as T cells, are educated to make this distinction during development.
Ph.D., Massachusetts Institute of Technology, 2015
cancer genetics, aneuploidy, genome dosage imbalances, systems biology
Nearly all tumors exhibit a condition known as aneuploidy—their cells contain the wrong number of chromosomes. We’re working to understand how aneuploidy impacts cancer progression, in hopes of developing therapies that can specifically eliminate aneuploid cancers while leaving normal cells unharmed.
Ph.D., Joint program of Massachusetts Institute of Technology and National University of Singapore, 2013
hematopoietic stem and progenitor cells, self-renewal, metabolism, hematopoietic malignancies
The research in my laboratory addresses a central question in hematopoiesis—which is how self-renewal and differentiation are properly balanced in the hematopoietic stem and progenitor cell population. We utilize both CRISPR/Cas functional genomic and chemical genomic approaches to identify novel regulators of self-renewal and aim to develop novel therapeutic strategies for hematopoietic diseases and malignancies.
RNA interference (RNAi) and CRISPR are widely used to functionally investigate mammalian genomes. It is our goal to develop and optimize these gene perturbation platforms to improve their effectiveness in understanding the biology of diseases.
Research Assistant Professor/Director Animal Imaging
I provide collaborative research support to CSHL researchers in the area of preclinical in vivo imaging. This includes access to a comprehensive range of imaging modalities, as well as provision of experimental guidance, training and imaging reagents. In addition, my lab develops new and impactful ways to image aspects of in vivo tumor biology that are broadly relevant to the development of new therapeutics and the research interests of the CSHL Cancer Center.
Ph.D., University of Leeds, 1984
proteomics, mass spectrometry, protein chemistry
Our genome can encode hundreds of thousands of different proteins, the molecular machines that do the work that is the basis of life. I use proteomics, a combination of protein chemistry, mass spectrometry and informatics, to identify precisely which proteins are present in cells - cells from different tissues, developmental stages, and disease states.
Research Assistant Professor/Head of Genomics Technology Development
Ph.D., Northwestern University, 2009
single cell, genomics, tumor microenvironment
Developing single-cell genomics technologies for applications related to cancer progression, immune surveillance, and discovery of rare novel cell types and transcriptional programs.
My research is aimed at uncovering the basis of sporadic genetic diseases such as autism, congenital heart defects and early-onset cancers.
Research Assistant Professor
Ph.D., Max-Delbrück Center for Molecular Medicine, Freie Universitaet, Berlin/Germany, 2009
transposons and endogenous retroviruses, small regulatory RNA, tRNA-fragments, epigenetics
Transposable elements make up half of our DNA. They control gene expression and have been a major evolutionary force in all organisms. The Schorn lab investigates how small RNAs identify and silence transposable elements when they become active during development and disease.
Research Assistant Professor & Director, CSHL Antibody and Phage Display Shared Resource
Ph.D., Cambridge University, 2006
cancer, drug discovery, antibody and protein engineering, chemical biology, signal transduction
Cells orchestrate proteins to conduct cell-cell communications and environment sensing in order to execute physiological functions. My lab investigates the mechanisms by which dysregulated signals cause diseases such as cancer, and we are developing therapeutics based on these mechanisms.
Genetics contribute to Autism in large degree. Modern genetics research demands an interdisciplinary approach to interpreting data generated from various high-throuput technologies. We are developing computational and statistical methods to analyze genomic data, with the goal of identifying mechanisms that cause genetic changes underlying autism.
WSBS Professor & Dean Lita Annenberg Hazen Dean
Ph.D., University of Edinburgh, 1989
My major areas of interest are gene regulation and the history of molecular biology.
population genetics, bioinformatics, cancer, stochastic processes, statistical mechanics and information theory
The biological landscape is made up of millions of variables that interact in complex and often seemingly random ways. I am applying principles from physical and computational sciences to the study of biology to find patterns in these interactions, to obtain insight into population genetics, human evolution, and diseases including cancer.
My lab studies the neurobiological principles underlying cognition and decision-making. Using state-of-the-art technologies, we interrogate neural circuits in rodents as they perform a task. We validate our findings with analogous tasks in humans. We hope to define the neural circuits underlying decisions that will inform the development of new therapies for psychiatric diseases.
Two challenges in cancer biology guide my work: first, how do tumors become addicted to certain gene products, and second, how do tumors develop resistance to anti-cancer drugs. I focus on the epidermal growth factor receptor (EGFR), which is both addictive when mutated and a common source of drug resistance. We are also identifying new targets for the treatment of lung cancer.