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Faculty

Valerie A. Arboleda

Associate Professor, Pathology and Laboratory Medicine
Associate Professor, Human Genetics

www.arboledalab.org

We are interested in leveraging multiomics based analysis to understand human disease

Email

vaa2001@g.ucla.edu

Office

BSRB 346

Themes: Integrative mechanistic modeling and experimentation

Amjad Askary

https://amjad.mcdb.ucla.edu/

We strive to find simple principles that are used during embryonic development to make complex tissues like the mammalian retina. To this aim, we develop innovative tools to monitor, characterize, and manipulate cells. We leverage both our methods and our findings to make better therapeutic strategies and molecular diagnostics.

amjada@ucla.edu

TLSB 5139

Themes: Complex datatype analysis, Experimental technologies development

Mehdi Bouhaddou

Assistant Professor, Microbiology Immunology and Molecular Genetics

bouhaddoulab.org

The Bouhaddou Lab dissects biochemical signaling circuits, attempting to understand how signaling network connectivity and dynamics impact cell fate outcomes. Cellular signaling can be envisioned to be the “mind” of the cell, generating the thoughts (i.e. signaling) that eventually turn into actions (i.e. cellular phenotypes). We are specifically interested in understanding how viruses impact host signaling networks and cellular phenotypes, employing quantitative approaches to systematically compare how different viruses hijack host phosphorylation signaling systems. Although we are mostly focused on viruses, our approaches are disease-agnostic, with applications to other areas of biology, including cancer and the environment.

mehdibouhaddou@gmail.com

Boyer 510G

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis

Tom Chou

Professor, Computational Medicine
Professor, Mathematics

https://www.math.ucla.edu/~tchou/

Stochastic processes and modeling from cell biophysics to population, tissues, and evolution

tomchou@ucla.edu

LSB 5209

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis

Hilary Coller

Professor, Molecular, Cell and Developmental Biology
Professor, Biological Chemistry

https://collerlab.dgsom.ucla.edu/

Our laboratory is investigating the state of cellular quiescence in which cells exit the proliferative cell cycle reversibly. We also investigate the quiescent state in the context of wound healing and cancer. We perform integrative mechanistic modeling and experimentation in our to build quantitative models of molecular changes with quiescence and experimentally test them.

hcoller@ucla.edu

TLSB 5145

Themes: Integrative mechanistic modeling and experimentation

Eric J Deeds

Professor, Integrative Biology and Physiology
Vice Chair, Life Sciences Core

https://deedslab.ibp.ucla.edu

Research in the Deeds lab is focused on understanding the dynamics and function of complex molecular networks within cells. We use a variety of approaches to study this problem, including developing new data analytic tools, supervised and unsupervised machine learning, mathematical modeling, biophysical modeling, and experiments. See our website (https://deedslab.ibp.ucla.edu) for more details!

deeds@ucla.edu

Boyer 570

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis

Elisa Franco

Professor, Mechanical and Aerospace Engineering
Professor, Bioengineering

https://www.seas.ucla.edu/francolab

Biomolecular condensates, RNA nanotechnology, computational modeling

efranco@seas.ucla.edu

Engineering IV 38-137 P

Themes: Integrative mechanistic modeling and experimentation, Experimental technologies development

Thomas Graeber

Professor, Molecular and Medical Pharmacology

https://systems.crump.ucla.edu

Systems biology and mathematical modeling of cancer signaling, metabolism, genomic instability and cell state plasticity. Development of integrative omics analysis. Iterative experimentation and analysis.

tgraeber@mednet.ucla.edu

CNSI 4341

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis

Alexander Hoffmann

Professor, Microbiology, Immunology and Molecular Genetics

signalingsystems.ucla.edu

We are interested in how the signaling networks of immune cells control their dynamic behavior, how heterogeneity may degrade fidelity but serve biological functions. We are focused on the dynamics innate immune responses and innate immune memory of macrophages, and how the dynamics control of B-cell evolution control antibody responses. We use knowledge-based and data-driven computational modeling, and cutting edge experimental approaches of live-cell imaging and ‘omic technologies.

ahoffmann@ucla.edu

Boyer 570

Themes: Integrative mechanistic modeling and experimentation

Weizhe Hong

Professor, Neurobiology
Professor, Biological Chemistry
Professor, Bioengineering

hong-lab.org

Social interactions between individuals and among groups are a hallmark of human society and are critical to the physical and mental health of a wide variety of species including humans. The central goal of our lab is to study the fundamental principles of how social behavior is regulated in the brain. We study how neural circuits and the underlying computation regulate social behavioral decisions within a single brain as well as how emergent inter-brain neural properties arise from social interactions between individuals. We take a multi-disciplinary approach and use a variety of experimental and computational technologies across molecular, circuit, and behavioral levels.

whong@ucla.edu

CHS 77-200K

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Neil Lin

Assistant Professor, Mechanical and Aerospace Engineering
Assistant Professor, Bioengineering

http://linlab.seas.ucla.edu

Our research applies a systems biology approach to explore the mechanobiological processes that drive cellular behavior. By engineering mechanical stimuli, such as cell adhesion and traction forces, with quantitative imaging and epigenetic analysis, we decode how cells respond to physical cues. We aim to uncover the molecular mechanisms that regulate cell motility, differentiation, and gene expression, ultimately advancing our understanding of tissue development and disease progression.

neillin@g.ucla.edu

Engineering IV 48-121B

Themes: Integrative mechanistic modeling and experimentation, Experimental technologies development

Aldons J. Lusis

Professor, Human Genetics
Professor, Microbiology Immunology and Molecular Genetics

https://lusis.genetics.ucla.edu/

Our lab uses natural genetic variation across inbred mouse strains to help dissect factors contributing to complex cardio-metabolic traits, including atherosclerosis, heart failure and fatty liver disease.

jlusis@mednet.ucla.edu

MRL 3-730

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Aaron Meyer

Associate Professor, Bioengineering

https://asmlab.org

I am interested in how we can integrate experimental and computational techniques to measure, model, and therapeutically manipulate cell-to-cell communication. I primarily focus on models of multivalent and multi-specific interactions to design and optimize immune therapies. For example, previous work in the lab has shown how antibodies interact with the innate immune system to better predict their protective effect and found new ways to design therapeutic cytokines with better selectivity.

ameyer@ucla.edu

Engineering V 4121G

Themes: Integrative mechanistic modeling and experimentation, Experimental technologies development

Matteo Pellegrini

Professor, Molecular, Cell and Developmental Biology

pellegrini.mcdb.ucla.edu

We are interesting in the development of methods for the analysis of genetic, epigenetic and transcriptomic data. Our focus has been on data generated using next generation sequencing.

matteop@g.ucla.edu

TLSB 5000D

Themes: Experimental technologies development

Noa Pinter-Wollman

Professor, Ecology and Evolutionary Biology

https://pinterwollmanlab.eeb.ucla.edu/

Many biological systems are complex aggregates of multiple agents working together towards collective, higher-order goals, and evolution acts on variation in these emergent collective properties. There is no central control dictating the activities of members in the assembly. Instead, agents use local signals that determine their behavior and are received through an intricate interaction network resulting in collective phenotypes. The Pinter-Wollman lab examines the emergence of collective outcomes by combining field and lab studies with computer simulations, theoretical work, image analysis, and social network analysis.

amjada@ucla.edu

Botany 310H

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Kathrin Plath

Professor, Biological Chemistry

https://plathlab.dgsom.ucla.edu

Our lab focuses on understanding how genes are turned on and off, how cells maintain their identity, how they can be reprogrammed to a younger, pluripotent stem cell state, the regulatory mechanisms that differ between males and females, and how tissues develop. We contribute to groundbreaking advancements in stem cell biology, developmental biology, epigenetics, reprogramming and X-chromosome biology, invent cutting-edge technologies to study chromatin dynamics and single cell epigenomics, transcriptomics, and secretomics. We generate extensive omics data sets that we analyze with cutting-edge approaches.

kplath@mednet.ucla.edu

BSRB 390B

Themes: Complex datatype analysis, Experimental technologies development

Amy Rowat

Associate Professor, Integrative Biology and Physiology

https://legacy.ibp.ucla.edu/research/rowat/RowatLab.html

The Rowat Lab studies cells as materials. We seek to translate our discoveries in cellular mechanobiology to applications from human health to the foods that we eat.

rowat@ucla.edu

TLSB 1125

Themes: Complex datatype analysis, Experimental technologies development

Danielle Schmitt

Assistant Professor, Chemistry and Biochemistry

https://dlschmitt.chem.ucla.edu

The Schmitt Lab in the UCLA Department of Chemistry and Biochemistry takes an interdisciplinary approach to study regulation of cellular metabolism. We develop fluorescent protein-based genetically encoded reporters for metabolites, amino acids, and kinases that regulate metabolism. We use these microscopy-based tools to study how metabolism is organized in space and time in single cells. We aim to understand how metabolism is regulated in healthy cells and perturbed in disease.

dlschmitt@chem.ucla.edu

Themes: Integrative mechanistic modeling and experimentation, Experimental technologies development

Pavak Shah

Assistant Professor, Molecular, Cell and Developmental Biology

https://sites.lifesci.ucla.edu/mcdb-shah/

Quantitative studies of early animal development. We use light microscopy, computer vision, machine learning, and modeling to study the regulation and dynamics of cell fate specification and embryogenesis.

pavak@ucla.edu

TLSB 5000C

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Jennifer Wilson

Assistant Professor, Bioengineering

https://research.seas.ucla.edu/computational-systems-pharmacology/

The lab simulates drug-induced cellular effects using protein-protein interaction network models and calibrates those effects to data derived from patients using the Electronic Health Record. Our group uses this combination of cellular models and bioinformatics to understand oncology and neurodegeneration.

jenniferwilson@g.ucla.edu

Engineering V 4121D

Themes: Integrative mechanistic modeling and experimentation, Experimental technologies development

Roy Wollman

Professor, Integrative Biology and Physiology
Professor, Chemistry and Biochemistry

Interim Home Area Director

https://wollmanlab.ucla.edu

We are developing spatial transcriptomics technology to connects annatomy to physiology. Our focus is on imaging based approaches that utilize hybridization with large oligonucleotide pools. We are also interested in developing theory on cellular variability and tissue organization utilizing information theory and mechanistic modeling.

rwollman@g.ucla.edu

Boyer 540

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Xinshu (Grace) Xiao

Professor, Integrative Biology and Physiology
Maria R. Ross Chair

https://xiaolab.ibp.ucla.edu/

We are a hybrid lab of computational and experimental RNA biology. The overarching goals of our research are to understand how the transcriptome and epitranscriptome are controlled by the intricate network of genetic factors, RNA elements, and RNA-binding proteins, and how such regulation contributes to neurological diseases and cancer.

gxxiao@ucla.edu

TLSB 2000E

Themes: Complex datatype analysis, Experimental technologies development

Xia Yang

Professor, Integrative Biology and Physiology

https://yanglab.ibp.ucla.edu

Our lab develops and applies multitissue multiomics approaches to model gene networks affected in complex human diseases, ranging from cardiometabolic diseases to neurological and psychiatric disorders. The disease networks are used to identify key regulatory genes and therapeutic agents.

xyang123@ucla.edu

TLSB 2000C

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis

Yi Yin

Assistant Professor, Human Genetics

https://recombination.dev

We’re interested in developing and applying new single cell sequencing methods to study genetic recombination and resulting structural variations. We’re also using functional genomics approaches to study genetic variants that regulate genome instability.

yeastyin@g.ucla.edu

Gonda 6309

Themes: Integrative mechanistic modeling and experimentation, Complex datatype analysis, Experimental technologies development

Qing Zhou

Professor, Statistics and Data Science

https://faculty.stat.ucla.edu/zhou/

We develop statistical and computational methods for efficient analysis of large-scale high-throughput genomic data. We employ model-based and machine learning methods to make statistical and causal inference from these data. Our goal is to understand the causality in gene regulation and decode regulatory circuits by integrating RNA-seq data, protein binding data, chromatin interaction data, and DNA sequence data.

zhou@stat.ucla.edu

Math Sciences 8979

Themes: Complex datatype analysis