Our research lab is dedicated to advancing the field of bioinformatics and computational analysis by developing innovative methods tailored for the analysis of next generation sequencing data in complex diseases. Our lab actively engage in comparative network analysis of various cancer subtypes. Our primary focus lies in designing and developing innovative computational tools related to network biology and variant visualizations. By applying bioinformatics techniques, we aim to unravel the intricate genetic architecture of complex diseases, with a particular focus on cancer, within the framework of network biology.


1) Genetics of complex diseases:

Our research group specializes in the application of advanced bioinformatics methods to gain a comprehensive understanding of the intricate genetic architecture underlying complex diseases, with a particular emphasis on cancer.

By leveraging state-of-the-art computational approaches and innovative data analysis techniques, we strive to unravel the complex molecular mechanisms that drive the development and progression of cancer. Our research delves deep into the genetic landscape of cancer, aiming to identify key genetic alterations, biomarkers, and potential therapeutic targets.

Through the integration of diverse genomic data sets, such as next-generation sequencing data, transcriptomics, and epigenetics, we aim to elucidate the underlying genetic and molecular basis of cancer, facilitating the development of personalized treatment strategies and improving patient outcomes.

Our research endeavors contribute to the broader field of bioinformatics and genomics, advancing our understanding of complex diseases and paving the way for innovative approaches in cancer research and precision medicine.


2) Next generation sequencing data:

Our expertise lies in the comprehensive management and analysis of next-generation sequencing (NGS) data, alongside our ability to construct customized pipelines dedicated to deep sequencing, with the ultimate goal of identifying causal variants. Specifically, we have focused our efforts on the analysis of various types of sequencing data, including whole genome genotyping, whole genome sequencing, targeted sequencing, and whole exome sequencing.

Through our robust capabilities, we enable the extraction of invaluable insights from the vast amounts of NGS data. By leveraging advanced computational techniques and tailored pipelines, we aim to unravel the complexities of the genome and pinpoint the causal variants that underlie various biological phenomena.

Our commitment to cutting-edge analysis methodologies and the utilization of diverse sequencing data types positions us at the forefront of genomics research, empowering us to contribute significantly to the understanding of genetic variation and its impact on human health.


3) Database building:

Our research group is dedicated to the development of cutting-edge databases and bioinformatics tools designed to visualize and analyze genomic data, facilitating comprehensive insights into complex medical conditions. Notably, we have created two significant databases, namely the Database for Preterm Birth (dbPTB) and the Database for Preeclampsia (dbPEC).

Both dbPTB and dbPEC provide a comprehensive integration of genes, genetic variations, pathways, and associated published literature, offering a holistic view of the underlying factors and mechanisms involved in preterm birth and preeclampsia.

The significance of our work is reflected in the recognition and dissemination of our databases. dbPTB has been hosted on various platforms, including the prestigious Genomics & Health Impact website of the Centers for Disease Control and Prevention (CDC). On the other hand, dbPEC garnered substantial attention, with its publication in a highlighted article in Obstetrics and Gynecology in 2014, accompanied by an editorial that underscored its importance.


4) Developing network biology analysis and variant visualization tools:

Our research focuses on the development of state-of-the-art bioinformatics tools and machine learning applications to address critical challenges in genomics and network biology. One notable tool we have created is Visualization of Variants (VIVA), which integrates the functionalities of existing tools into a unified command, enabling interactive evaluation and sharing of genomic data. Notably, VIVA outperforms existing tools in terms of speed and efficiency.

In addition to tool development, we employ machine learning techniques to extract valuable insights from the vast literature on preterm birth and preeclampsia, shedding light on the genetic underpinnings of these complex conditions.

Furthermore, our expertise extends to the field of protein-protein interactions, where we have developed advanced network analysis and visualization tools. One such tool is Proteinarium, a cutting-edge implementation that enables multi-sample protein-protein interaction (PPI) analysis and visualization. Proteinarium enhances our ability to explore and understand intricate protein interaction networks, empowering researchers with comprehensive insights into the complex biological mechanisms at play.


5) Bioinformatics applications on protein structures and comparative functional genomics:

Our research group is dedicated to the exploration of bioinformatics applications in the domains of protein structures and comparative functional genomics. Our primary focus revolves around investigating the impact of single nucleotide polymorphisms (SNPs) on protein structures, as well as conducting in-depth analysis of comparative functional genomics on protein structures.

By utilizing advanced computational techniques, we delve into the intricate relationship between SNPs and protein structures, aiming to unravel how these genetic variations influence protein function, stability, and interactions. This knowledge contributes to a deeper understanding of the molecular basis of genetic diseases and provides insights into potential therapeutic interventions.

Additionally, our research extends to comparative functional genomics analysis, where we leverage computational methods to compare and analyze protein structures across species. This allows us to identify conserved regions, functional motifs, and evolutionary relationships, shedding light on the fundamental principles that govern protein function and evolution.

Through our bioinformatics-driven approach, we aim to uncover critical insights into the interplay between genetic variations, protein structures, and functional genomics, ultimately advancing our understanding of complex biological systems and facilitating the development of novel therapeutic strategies.

Funded Research

The Legorreta Cancer Center, Brown University, Pilot Grant.
Network Analysis Approach to Discover Potential Cancer Drug Targets
March 1, 2022 – August 31, 2023
Role: Co-PI

Burroughs Wellcome Fund
July 15, 2021 – April 30, 2023
Computational Approaches to the Genetics of Complex Diseases: Proteinarium – A network analysis of complex diseases.
Role: PI

Pilot Research Awards from the William and Mary Oh-William and Elsa Zopfi Professorship in Pediatrics for Perinatal Research
July 1, 2019 – June 30, 2020
Bioinformatic and glycomic approach to identifying potential virulence pathways of Candida parapsilosis
Role: Co-PI

William and Mary Oh – William and Elsa Zopfi Professorship in Pediatrics for Perinatal Research.
 June 1, 2018 – May 31, 2019
Bioinformatic approach to identifying potential virulence pathways of Candida parapsilosis.
Role: Co-PI

NIH, COBRE: Center for Computational Biology of Human Disease  #1P20GM109035-01A1 06/01/2016-2/28/2021
Computational Genomics of Preeclampsia
Role: Project Leader

Pilot Project Program of the COBRE for Perinatal Biology Uzun (PI) 09/01/2015-04/30/2016 
Transcriptome Profiling of Extracellular Vesicles Defines Molecular Phenotypes of Preeclampsia
Role: PI

National Foundation March of Dimes  #21-FY14-154 Padbury (PI) 03/01/2014-02/28/2017
Bioinformatics and Targeted Resequencing in Preterm Birth.
Role: Co-I

Rhode Island Foundation  Uzun (PI) 03/01/2014-02/28/2015 
Targeted Exome Sequencing of Extreme Phenotypes of Preterm Birth.
Role: PI

COBRE Center for Cancer Signaling Networks Pilot Project Fund Uzun (PI) 06/01/2013-03/31/2014
Targeted sequencing for preterm birth associated genes.
Role: PI

NIH, 1R21HD070177-01A1 Triche And Dewan (PIs) 04/01/2012-03/31/2014
Fetal Genetic Contributions to Preeclampsia.
Role: Co-I

COBRE Center for Cancer Signaling Networks Pilot Project Fund Uzun (PI) 07/01/2011-03/31/2012
Targeted Genomic Resequencing in Preterm Birth.
Role: PI

National Foundation March of Dimes #21-FY08-563 Padbury (PI) 03/01/2009-02/28/2012
Preterm Birth: A Novel Bioinformatics and Genomics Approach.
Role: Postdoctoral Researcher/Co-Investigator

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