Labs in computational biology use math, statistics and computer science to answer biological questions.
Labs in This Area
Analyzing high–throughput genomic data in the context of biological networks
I am a computational biologist with an interest in the development of methods for integrative, systems-level analysis of high-dimensional genomic and proteomic data. These methods incorporate bioinformatics information with experimental data to characterize the networks of interactions that lead to the emergence of complex phenotypes, particularly cancers.
For more information, visit the faculty profile of Rosemary Braun, PhD, MPH.
See Dr. Braun's publications in PubMed.
Studying molecular motors and cell motility
Movement is a fundamental characteristic of life. Cell movement is critical for normal embryogenesis, tissue formation, wound healing and defense against infection. It is also an important factor in diseases such as cancer metastasis and birth defects. Movement of components within cells is necessary for mitosis, hormone secretion, phagocytosis and endocytosis. Molecular motors that move along microfilaments (myosin) and microtubules (dynein) power these movements. Our goal is to understand how these motors produce movement and are regulated. We wish to define their involvement in intracellular, cellular and tissue function and disease—with the long-term goal of developing therapies for the treatment of diseases caused by defects in these molecular motors.
Our work involves the manipulation of myosin and dynein function in the single celled eukaryote Dictyostelium, cultured mammalian cells and transgenic and knockout mice. Yeast two-hybrid screens to identify proteins that interact with or regulate myosin and dynein and characterization of gene expression are being used to define the pathways regulating myosin and dynein. To analyze the biological significance of myosin and dynein, we use confocal and digital microscopy of living cells, analysis of cell movement, vesicle transport and cell division. We employ biochemical techniques including heterologous expression, enzyme purification and characterization and analysis of how phosphorylation state affects physiological function. We are pursuing signal transduction studies to understand the physiologically important pathways that regulate cell motility and biophysical studies such as in vitro motility assays to understand how these molecular motors function at the molecular level.
For lab information and more, see Dr. Chisholm's faculty profile.
See Dr. Chisholm's publications on PubMed.
Contact Dr. Chisholm at 312-503-3209.
Developing software algorithms and research infrastructure for computational pathology
Our research develops computational approaches to analyze data generated in the pathology lab. Our goal is to improve diagnostics, to advance clinical translation of computational pathology research, and to provide investigators with tools to generate new insights from complex data. To accomplish these goals we focus on:
- Fundamental research in machine-learning and artificial intelligence
- Development of software infrastructure for computational pathology
- Generating annotated datasets for training and validation of computational pathology algorithms
We apply these techniques to a number of problems including:
- Measuring immune response in cancer and development of immuno-oncology biomarkers
- Prediction of clinical outcomes from genomic and digital pathology data
- Classification of hematologic malignancies
Translational Bioinformatics and Cancer Genomics
Research in our lab focuses on developing informatics solutions to solve problems in biology and medicine. Current projects are focused on two closely related areas: (A) mammalian gene regulation at isoform-level and (B) isoform-level transcriptional networks in brain development and brain tumors. The overarching goal of his lab is to translate Big Data from multiple high dimensional (-omic) platforms (e.g., NextGen sequencing) to derive experimentally interpretable and testable discovery models towards genomics-based clinical decision support systems for personalized cancer therapy. Our group is developing bioassays that can rapidly identify biomarkers from human tissue and blood samples. Towards these goals, our group applies state-of-the-art statistically rigorous data-mining methods and NextGen sequencing based experimental procedures in a systems biology setting.
Our research program is interdisciplinary in nature with a complement of experimental investigation. The current projects of our laboratory are:
- Informatics platform for mammalian gene regulation at isoform-level
- Isoform-level transcriptional networks in brain development and brain tumors
- Molecular classification of cancers
Coupled with advances in high throughput technologies, our computational modeling work seeks to address key outstanding issues in mammalian genomics and cancer. We currently maintain online databases (e.g., MPromDb – Mammalian Promoter Database), programs for NextGen sequence analysis (e.g., IsoformEx, Isoform level gene expression estimation from RNA-seq data; TPD – Modeling Transcription Factor Binding Site Profiles from ChIP-Seq Data; NPEBseq: Differential Expression analysis based on RNA-seq data; and Data-mining methods for molecular stratification of cancers (e.g., PIGExClass – Platform-independent Isoform-level Expression based classification-system).
For more information, visit the faculty profile of Ramana Davuluri, PhD.
See Dr. Davuluri's publications in PubMed.
Research Assistant Professors:
Yingtao Bai; Hong-Jian Jin
Segun Jung; Majoh Kandpal
Investigating the structure, function, pharmacology and molecular genetics of ion channels and channelopathies
Ion channels are ubiquitous membrane proteins that serve a variety of important physiological functions, provide targets for many types of pharmacological agents and are encoded by genes that can be the basis for inherited diseases affecting the heart, skeletal muscle and nervous system.
Dr. George's research program is focused on the structure, function, pharmacology and molecular genetics of ion channels. He is an internationally recognized leader in the field of channelopathies based on his important discoveries on inherited muscle disorders (periodic paralysis, myotonia), inherited cardiac arrhythmias (congenital long-QT syndrome) and genetic epilepsies. Dr. George’s laboratory was first to determine the functional consequences of a human cardiac sodium channel mutation associated with an inherited cardiac arrhythmia. His group has elucidated the functional and molecular consequences of several brain sodium channel mutations that cause various familial epilepsies and an inherited form of migraine. These finding have motivated pharmacological studies designed to find compounds that suppress aberrant functional behaviors caused by mutations.
- Discovery of novel, de novo mutations in human calmodulin genes responsible for early onset, life threatening cardiac arrhythmias in infants and elucidation of the biochemical and physiological consequences of the mutations.
- Demonstration that a novel sodium channel blocker capable of preferential inhibition of persistent sodium current has potent antiepileptic effects.
- Elucidation of the biophysical mechanism responsible for G-protein activation of a human voltage-gated sodium channel (NaV1.9) involved in pain perception.
- Investigating the functional and physiological consequences of human voltage-gated sodium channel mutations responsible for either congenital cardiac arrhythmias or epilepsy.
- Evaluating the efficacy and pharmacology of novel sodium channel blockers in mouse models of human genetic epilepsies.
- Implementing high throughput technologies for studying genetic variability in drug metabolism.
- Implementing automated electrophysiology as a screening platform for ion channels.
For lab information and more, see Dr. George’s faculty profile
See Dr. George's publications on PubMed.
Contact Dr. George at 312-503-4892.
Health care outcome assessments
Dr. Gershon is a leading expert in the application of Item Response Theory (IRT) in individualized and large scale assessments. He has developed item banks and Computerized Adaptive Testing (CAT) for educational, clinical, and health applications - including cognitive, emotional, and motor applications. He is currently principal investigator on these projects with the NIH: NIH Toolbox for the Assessment of Neurological Function and Behavior, the NIH Roadmap Patient – Reporting Outcomes Measurement Information System (PROMIS) Technical Center, the National Institutes on Aging Genetic Norming project, and the National Children's Study: Vanguard Study(South ROC). He is also co-investigator and measurement development expert on numerous smaller projects including the NINDS sponsored project “Quality of Life Outcomes in Neurological Disorders” (Neuro-QOL), and the cancer-specific supplement to PROMIS.
For more information visit the faculty profile of Rich Gershon, PhD.
See Dr. Gershon's publications in PubMed.
Environmental, genetic and epigenetic risk factors for disease
Dr. Hou’s research interest lies in integrating traditional epidemiologic methods with the ever-advancing molecular techniques in multi-disciplinary research focusing on identifying key molecular markers and understanding their potential impact on disease etiology, detection and prevention.
Dr. Hou’s major research efforts to date have focused on two areas: 1) identification of risk factors that may cause chronic diseases; and 2) identification of biomarkers that serve as indicators of an individual’s past exposure to disease risk factors and/or predict future disease risks and/or prognosis. The environmental/lifestyle risk factors that Dr. Hou has studied include air pollution, pesticides, overweight, physical inactivity and reproductive factors in relation to chronic diseases. The biomarkers that Dr. Hou has investigated include genetic factors (i.e., polymorphisms, telomere length shortening, mitochondria DNA copy number variations) and epigenetic factors (i.e., DNA methylation, histone modifications and microRNA profiling). Her over-arching research goal is to understand the biological mechanisms linking environmental risk factors with subclinical or clinical disease development to ultimately lead to development of effective strategies for prevention of chronic diseases.
In addition to being a PI of several NIH funded grants, Dr. Hou is the co-director and Co-PI of the Northwestern Consortium for Early Phase Cancer Prevention Trials of the Division of Cancer Prevention (DCP) Consortia, National Cancer Institute.
For more information visit the faculty profile of Lifang Hou, MD, PhD.
See Dr. Hou's publications in PubMed.
Dissecting the regulation of gene transcription and RNA translation underlying oncogenic processes.
Cancer happens through accumulated genetic mutations and epigenetic alternation in normal cells. With the advances of genomic technologies, we now can precisely characterize the genome-wide alternations of gene expression underlying oncogenic processes in a cost-effective and unbiased manner. My lab will use the combined experimental genomic technologies and computational modeling to examine the regulation of gene transcription and RNA translation during steps of oncogenesis. We aim at revealing novel cancer therapeutic targets and strategies for precision medicine and immunotherapy.
Currently, we are working on the following projects.
- Characterizing the transcriptional regulatory circuits mediating inflammation in the cancer microenvironment.
- Examining the genome-wide regulation of RNA translation in cancers.
- Defining the functional roles of non-canonical translation in lncRNAs, pseudogenes and 5’UTRs in cancers.
For lab information and more, see Dr. Ji's faculty profile.
See Dr. Ji's publications on PubMed.
Contact Dr. Ji at 312-503-2187.
Cardiovascular disease epidemiology, risk estimation and prevention
Dr. Lloyd-Jones’ research interests lie in cardiovascular disease epidemiology, risk estimation and prevention. A main focus of his research has been investigation of the lifetime risks for various cardiovascular diseases and factors that modify those risks. Other areas of interest include cardiovascular disease risk estimation using novel biomarkers, imaging of subclinical atherosclerosis and the epidemiology of hypertension. His clinical and teaching interests lie in general cardiology with a focus on prevention.
For more information, visit the faculty profile of Donald Lloyd-Jones, MD, ScM.
Machine learning, natural language processing, time series analysis, integrative genomic analysis and big data analytics, with a focus on medical and clinical applications
For more information visit Dr. Luo's faculty profile page
Genetic mechanisms responsible for inherited human diseases
My laboratory studies genetic mechanisms responsible for inherited human diseases including heart failure, cardiomyopathy, muscular dystrophy, arrhythmias, aortic aneurysms. Working with individuals and families, we are defining the genetic mutations that cause these disorders. By establishing models for these disorders, we can now begin to develop and test new therapies, including genetic correction and gene editing.
For lab information and more, see Dr. McNally's faculty profile
See Dr. McNally's publications on PubMed.
Email Dr. McNally
Design, developing, evaluating, and implementing technology-assisted behavioral and psychological interventions.
David C. Mohr, PhD, is the Director of the Northwestern University Center for Behavioral Intervention Technologies (CBITs). Dr. Mohr’s expertise is in the design, development, evaluation, and implementation of technology-assisted behavioral and psychological interventions. These technologies use mobile phones, tablets, computers, and sensors to support patient behaviors related to health, mental health, and wellness. In the area of development, Dr. Mohr’s primary expertise is in designing applications that can be deployed to phones and desktop computers aimed at treating mental health disorders. While many of these have been relatively standard applications, he is also developing methods of harnessing sensor data from the phone to identify user states that are relevant to the treatment of depression. A second area of development focuses on developing applications aimed at improving adherence to medications and medical regimens. These applications are being deployed in General Internal Medicine, Community Health Centers, and Psychiatry. Finally, Dr. Mohr examines methods of implementing behavioral intervention technologies in the healthcare settings. In general, behavioral intervention technologies are not effective in improving symptoms when delivered as standalone treatments. Dr. Mohr has developed and evaluated methods of providing low intensity coaching support to enhance the use and effectiveness of behavioral intervention technologies. These coaching models can use health professionals, lay people, and peers.
For more information visit the faculty profile of David Mohr, PhD.
See Dr. Mohr's publications in PubMed.
Clinical and translational research of life-threatening neurological diseases, particularly brain hemorrhage.
Intensive monitoring is a core function of an intensive care unit, and generates large amounts of data. In a neurologic unit, surveillance neuromonitoring is as important as vital signs and cardiac rhythm, yet there has been less clarity as to precisely what should be measured (biomarkers, imaging markers, serial examination scores) and its impact on complications and outcomes. We have established methods and models for the retrieval and analysis of data from the electronic health record for patients with stroke for a large registry that I have maintained over 10 years (Northwestern University Brain Attack Registry, NUBAR), which now includes >1,000 patients.
Research to improve patient outcomes is limited to endpoints we can reliably measure. Collaborating with Neuro-QOL, a platform for measuring Quality Of Life in neurological disorders, and the NIH Patient Reported Outcomes Measurement Information System (PROMIS) Statistical Center, we have shown web-based computer-adaptive testing by study staff, patients or family members are valid compared to the usual standard of a validated interview, have increased statistical power, and highlight aspects of HRQoL, such as cognitive function, that would otherwise be undetectable (supported by K23 HS023437). Further, these measures improve our statistical power to perform research that measurably improves patient-centered outcomes.
In a continuing project with Preventive Medicine faculty, we are using network analytic techniques to identify high-performing teams. Previous publications have established methods to identify which members of the health care team (e.g., physicians, pharmacists, nurses) interacted with the patient in the electronic health record. Then, a quantitative measure of the success of interactions is calculated on an outcome. In past research, likelihood to recommend scores were the outcome. Here, we used NUBAR’s recorded functional outcomes (e.g., independence, dependence, death), and established that the interactions of team members are an independent predictor of patient outcome after accounting for severity of injury. This research opens up new lines of research on how to design high-performing teams.
In short, the lab collaborates widely to leverage innovative techniques to improve treatments for patients with life-threatening neurologic injury.
Professor of Neurology
Research in the Savas lab is aimed at accelerating our understanding of the proteins and proteomes responsible for neurodevelopmental and neurodegenerative diseases.
We use biochemistry with discovery-based mass spectrometry to identify the protein perturbations which drive synaptopathies and proteinopathies. Groups of perturbed proteins serve as pathway beacons which we subsequently characterizes in hopes of finding new pathogenic mechanisms and potential future therapeutic targets.
Please see Dr. Savas' publications on PubMed.
Jeffrey N Savas, PhD
Assistant Professor in Neurology
Dr. Silverberg specializes in dermatoepidemiology with a focus on comorbidities and quality of life. His research interests include the patient- and population-based burden of inflammatory skin disease, particularly atopic dermatitis (eczema), contact dermatitis and photosensitive disorders.
1 - identify novel modifiable risk factors for inflammatory skin diseases and develop clinical and epidemiological interventions to prevent these disorders throughout the US population. This includes improving the understanding of the genetics and gene-environment interactions in adult atopic dermatitis.
2 - develop improved assessments for patients with chronic itch that can help us understand how best to reduce the itch, which is so life altering for patients.
3 - work toward improving the understanding of the direct and indirect burden of inflammatory skin diseases, including their relationship with other health conditions, such as cardiovascular disease.
In 2014, Dr. Silverberg founded Northwestern Medicine’s Multidisciplinary Eczema Center, and as its director, he has been able to advance research and test cutting-edge therapeutic approaches.
See Dr. Silverberg's publications on PubMed.
Email Dr. Silverberg
Behavioral risk factors
My laboratory conducts research on behavioral risk factors (obesity, poor quality diet, physical inactivity, tobacco use). We also develop cutting-edge technologies that support self-regulation and healthy behavior change. Finally, we create on-line learning tools to support skill mastery in evidence-based practice and team science.
View Dr. Spring's publications at PubMed.
Health care computing
My current research focuses on new ways to make health care computing more useful. This includes developing intuitive, novel Human Computer Interfaces (HCI) for health care, including working on the design of graphical icons for clinical applications, addressing data overload for clinicians and issues in affective computing. A related line of research is developing methods for the integration of clinic research computing into clinical care.
View Dr. Starren's publications at PubMed
Computational immunology - Using genomic approaches to study rheumatic disease.
The goal of the Winter Lab of Functional Genomics is to apply genomic approaches to study rheumatic disease. Led by Dr. Deborah Winter, a computational immunologist, we employ the latest technologies for assays, such as RNA-seq, ChIP-seq, ATAC-seq and single cell expression, to profile the transcriptional and epigenomic profiles of immune cells in health and disease. Our goal is to define the underlying regulatory networks and understanding how they respond to challenge, illness and injury. We are particularly interested in the role of macrophages in diseases such as scleroderma, rheumatoid arthritis and lupus. Previous research has addressed the impact of the tissue environment on resident macrophages and the role of microglia, CNS-resident macrophages, in brain development. Our research combines molecular and systems biology, biotechnology, clinical applications and computer science. We use both mouse models and patient samples to help us understand and test different systems. We are committed to high standards of analysis and are continually updating and training in innovative computational techniques. We are currently recruiting highly motivated individuals to join the lab.
For more information, visit the faculty profile of Dr. Winter.
View Dr. Winter's publications at PubMed
Contact Dr. Winter at 312-503-0535 or by email.
Epigenomics and 3D genome organization in the context of human diseases
1) Disease-causing variants: investigating the function of non-coding variant in the human genome and how they contribute to diseases such as cancer;
2) Cancer epigenomics: investigate epigenetic marks for certain types of cancer with a hope that it may eventually contribute to drug discovery.
3) 3D Genome Organization: Study the 3D structure of the genome organization by 5C/Hi-C, in particular the interactions between enhancers and their target gene promoters;
4) Use combination of current techniques to detect and validate structual variants in cancer genomes.
5) Comparative genomics: investigate the evolutionary landscape of cis-regulatory elements in the mammalian genome;
Techniques used in the lab
Bioinformatics : Determine TF occupancy, enhancer prediction, differential gene expression, 3D genome organization, GWAS.
Functional genomics: ChIP-Seq, RNA-Seq, Starr-Seq, Hi-C, Capture-C, CRISPR.
Please see Dr. Yue's publications in PubMed.
Contact Dr. Yue
Genetics and epigenetics of complex traits including risks for common diseases and drug response
For more information, visit Dr. Zhang's Faculty Profile page.