NIH Awards – 2018

Arnold

R01 – A Machine Learning Approach to Classifying Time Since Stroke using Medical Imaging

R21 – Predicting the Presence of Clinically Significant Prostate Cancer using Multiparametric MRI and MR-US Fusion Biopsy

Bui

T32 – Medical Imaging Informatics Training Grant

Chou

T32 – Systems in Integrative Biology

Coller

R01 – The Role of Stromal Autophagy in Cutaneous Melanoma

Ernst

DP1 – Deciphering the Relationship between Substance Use and Psychiatric Disorders from Whole Genome Sequencing Data

Eskin

R25 – Mathematical and Computational Approaches in High-Throughput Genomics Training

Graeber

R01 – Targeting Genomic Instability in Lethal Neuroendocrine Prostate Cancer

Hoffmann

R01 – The NFkB System in Dendritic Cells

R01 – Cell decision underlying B-cell immune responses

R01 – NFkB Signaling in Macrophages

R01 – Coordinated dynamic regulation and function of IRF transcription factors

R01 – Understanding dynamical coding by NFkB

R21 – Roles of RelB in tuning inflammatory and innate immune responses

Horvath

U01 – Validation and optimization of epigenetic clocks

Lohmueller

R35 – Population genomics of the selective effects of new mutations

Meyer

DP5 – Adapter-Layer RTK Signaling: Basic Understanding & Targeted Drug Resistance

U01 –Precision lung cancer therapy design through multiplexed adapter measurement

Ophoff

R01 – Genetic, Imaging, and Cognition study of Positive Valence Systems in Psychotic Syndromes

R01 – Joint genomic and statistical analyses of schizophrenia and bipolar to decipher genetic susceptibility

RF1 – Genetics of CSF Metabolites in Alzheimer Disease and other Brain Disorders

Pajukanta

R01 – Genomics of dyslipidemia in Mexicans

Pasaniuc

R01 – Integrative approaches for mapping the genetic risk of complex traits

Pellegrini

R01 – Enhancing the International Molecular Exchange (IMEx): Providing an Improved Community-Oriented Molecular Interactions Resource

T32 – Biomedical Big Data Training Grant

Ping

T32 – iDISCOVER: Integrated Data Science Training in CardioVascular Medicine

R35 – Omics Phenotyping for Identifying Molecular Signatures of the Healthy and Failing Heart: An Integrated Data Science Platform

Pinter-Wollman

R01 – Modeling how keystone individuals emerge and influence disease transmission

Qu

R01 – A population-based in silico platform for arrhythmia prediction

R01 – Mitochondria and arrhythmogenic calicum cycling dynamics in the heart

Rodriguez

R21- Development of a broad spectrum therapeutic against New World hemorrhagic fevers

R35 – Micro Electron Diffraction of Toxic and/or Infectious Macromolecular Nanoassemblies

Sankararaman

R35 – Statistical Models for Dissecting Human Population Admixture and its Role in Evolution and Disease

Wollman

R01 – The Spread of Noisy Information in Corneal Epithelial Wound Response Signaling

R01 – Reliable Signal Transduction

Xiao

U01 – Analysis of functional genetic variants in RNA processing and expression

R01 – Prioritization of splicing-altering genetic variants in Alzheimers disease

U01 – Informatic tools for single-nucleotide analysis of cancer RNA-Seq

U01 – Analysis of functional genetic variants in RNA processing and expression

Yang

R01 – DHA Reverses Gene Network Signatures of Fructose-induced Metabolic Syndrome

R01 – DHA Reverses Gene Network Signatures of Fructose-induced Metabolic Syndrome

R21 – Cell-specific novel genomic biomarkers of TBI pathology

Zhou

U01 – The UCLA Center in Early Detection of Liver Cancer

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NIH Awards – 2017

Chou T32 – NIGMS Systems & Integrative Biology

Eskin
R25 – Mathematical and Computational Approaches in High-Throughput Genomics Training
R25 – Undergraduate Research Experience in Neuropsychiatric Genomics
R00 – Genetic Influences on Human Cortical Development

Hoffmann
R01 – Coordinated Dynamic Regulation and Function of IRF Transcription Factors
R01 – Understanding Dynamical Coding by NFKB
R25 – NGS Data Analysis Skills for the Biosciences Pipeline
U01 –“Ribonomics” of Gene Regulation to Predict Innate Immune Responses

Horvath
U34 – The Epigenetics Leads to Age-Related Diseases (Gilga-Mesh) Network

Li
R01 – Robust Indentification and Accurate Quantification of RNA Transcripts on a System Wide Scale

Lohmueller
R35 – Population Genomics of the Selective Effects of New Mutations

Pajukanta
R01 – Genomics of Dyslipidemia in Mexicans
P01 – Systems Genomics of Metabolic Syndrome Traits

Pasaniuc
R01 – Integrative Approaches for Mapping the Genetic Risk of Complex Traits

Pellegrini
T32 – Biomedical Big Data Training Grant

Ping
R35 – Omics Phenotyping for Identifying Molecular Signatures of the Healthy and Failing Heart: An Integrated Data   Science Platform
U54 – A Community Effort to Translate Protein Data to Knowledge: An Integrated Platform

Qu
R01 – Mitochondria and Arrhythmogenic Calcium Cycling Dynamics in the Heart

Sankararaman
R00 – Statistical Methods to Infer Structure and Impact of Ancient Admixture

Sul
K01 – A Computational Genomics Approach to Identifying Roles of Rare Genetic Variants in Psychiatric Disorders and Gene Expression

Wang
R01 – Fast and Robust Methods for Large Scale Genotype Phenotype Association Study
U01 – Mining the Social Web to Monitor Public Health and HIV Risk Behaviors

Pinter-Wollman
R01 – Modeling How Keystone Individuals Emerge and Influence Disease Transmission

Wollman
R01 –The Spread of Noisy Information in Corneal Epithelial Wound Response Signaling
R01 – Reliable Signal Transduction

Xiao
R01 – Chemical Modulators of Nuclear Lamins
 R01 – Targeting HSP60 to Inhibit Creb-Medicated Gene Transcription
R21 – Targeting EWS-ATF1 in CCSST

Xing
R01 – Variation and Regulation of Alternative Splicing in Human Transcriptomes

Yang
R21 – Cell-Specific Novel Genomic Biomarkers of TBI Pathology
R01 – DHA Reverses Gene Network Signatures of Fructose-Induced Metabolic Syndrome

Yeates
S10 – Stopped-Flow Spectrometer