is a research group at Georgetown Lombardi Comprehensive Cancer Center, Georgetown University Medical Center
. Its goals are to develop analytical tools for mass spectrometry-based proteomics, metabolomics, and glycomics studies and to apply the tools for biomarker discovery and systems biology research.
Our research group
is composed of two components (a wet lab and a computational lab). The wet lab is focused on collection, storage, and processing of human serum and plasma samples prior to mass spectrometric data acquisition by LC/GC-MS.
In addition to a variety of LC-MS systems accessible to us at Georgetown Lombardi's Proteomics and Metabolomics Shared Resource, the following instruments are available in our wet lab:
Agilent 1260 Infinity HPLC system
LECO Pegasus HT GC-TOF MS system
Agilent GC-MS with both EI and CI sources
The combination of GC/MS and LC/MS technologies will provide complementary approaches to analyze a broad class of metabolites. The computational lab develops signal processing and machine learning methods for analysis of omics data generated in our wet lab or in other collaborating labs.
is focused on building a pipeline for mass spectrometry-based proteomic, metabolomic, and glycomic biomarker discovery studies. Our long-term goal is to find and validate candidate cancer biomarkers in human serum and plasma samples. Our pipeline involves experimental design, sample collection, sample storage, sample preparation, mass spectrometric data acquisition, data preprocessing, statistical analysis, biomarker identification and validation. Our computational group is engaged in developing signal processing and machine learning methods needed for the pipeline, while our wet lab conducts method development and sample preparation needed for mass spectrometric experiments.
are funded by grants from the National Institutes of Health (NIH)
to develop analytical tools for mass spectrometric data analysis and to find and validate metabolic, peptide, and glycan biomarkers for early detection of hepatocellular carcinoma. We collaborate with clinicians, basic scientists, computational scientists, and experts in mass spectrometry, proteomics, metabolomics, and glycomics.
In particular, we collaborate with Computational Bioinformatics and Bioimaging Laboratory of Virginia Tech
; Proteomics and Mass Spectrometry Laboratory of University of South Alabama
; Texas Tech
; and Molecular Genetics/Proteomics Core, Children National Medical Center
|©2010-2013 Ressom Lab Suite 173, Building D 4000 Reservoir Rd,N.W., Washington, D.C. 20057-1484
Habtom W. Ressom, Ph.D. Associate Professor
Dr. Ressom received a Ph.D. in Electrical Engineering from the University of Kaiserslautern, Germany in 1999. Prior to joining Georgetown University in 2004, he was an Assistant Professor of Electrical and Computer Engineering at the University of Maine, where he applied artificial neural networks, fuzzy logic, and evolutionary computing for microarray gene expression data analysis, DNA base calling, ocean color remote sensing, and industrial process control. His research at Georgetown University focuses on cancer biomarker discovery and systems biology by analysis of omics data. Specifically, he uses label-free LC-MS methods to search for candidate peptide, glycan, and metabolic biomarkers in serum and plasma. His laboratory develops signal processing, statistical, and machine learning methods to analyze LC-MS data and to integrate omics data for biomarker discovery and systems biology research. His laboratory is funded by grants from the National Science Foundation and the National Institutes of Health. Dr. Ressom is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and a co-director of the Lombardi Comprehensive Cancer Center's Genomics and Epigenomics Shared Resource, which provides services for various studies including DNA sequencing, fragment analysis, gene expression, microRNA, methylation, and SNP genotyping.
E-mail: email@example.com Office: 175 Building D Phone:202-687-2283
Rency S. Varghese, M.S. Research Associate
Ms. Varghese obtained her M.S. degree in Electrical Engineering from University of Maine, Orono in 2004 and her Bachelors degree in Electrical and Electronics Engineering from College of Engineering, Trivandrum, India in 1999. She worked as software engineer/consultant for two years in India. Before joining LCCC in 2004, she worked as Research Assistant during her study at University of Maine, where she applied methods such as artificial neural networks, fuzzy logic, and evolutionary computing for microarray data analysis and DNA base calling. She is currently working on the development of machine learning methods for analysis of mass spectrometry data.
E-mail: firstname.lastname@example.org Office: 174 Building D Phone:202-687-7369
Cristina Di Poto, Ph.D. Postdoctoral Research Fellow
Dr. Di Poto received her Ph.D. in Biochemistry from University of Pavia, Italy in 2008. She is currently focused on developing optimal sample preparation, fractionation, mass spectrometry data analysis and interpretation in human proteomics.
E-mail: email@example.com Office: W325 Research Building Phone:202-687-2926
Jinlian Wang, Ph.D. Postdoctoral Research Fellow
Dr. Wang received her Ph.D. in Artificial Intelligence from College of Electrical Information and Control Engineering, Beijing University of Technology, China in 2008.?She was a post doctoral fellow at Lombardi Comprehensive Cancer Center, Georgetown University Medical Center in 2009, where she built a web system for predicting O-GlcNAcylated proteins and sites using machine learning methods. She also developed a biomedical event annotation tool, applied to biomedical literature mining. She is interested in cancer biomarker discovery and integration of multiple omics data for network and pathaway analysis.
E-mail: firstname.lastname@example.org Office: 174 Building D Phone:202-687-3045
Bin Zhou, M.S. Research Assistant
Bin Zhou received his B.S. degree from Wuhan University, China and M.S. degree from Zhejiang University, China both in Electrical Engineering. Currently a PhD student at Virginia Tech, his research interest focuses on developing signal processing and machine learning methods for image processing and analysis of metabolomic data.
E-mail: email@example.com Office: 173 Building D Phone:202-687-3381
Tsung-Heng Tsai, M.S. Research Assistant
Tsung-Heng Tsai received his B.S. in Power Mechanical Engineering from the National Tsing Hua University in 2003, and his M.S. in Electrical and Control Engineering from the National Chiao Tung University in 2005. During 2007-2009, he was a research assistant at the Institute of Information Science, Academia Sinica. He is currently a Ph.D. student at Virginia Tech. His research interest is proteomics data analysis with statistical and machine learning approaches.
E-mail: firstname.lastname@example.org Office: 176 Building D Phone:202-687-9396
Mohammad R. Nezami Ranjbar, M.S. Research Assistant
Mohammad R. Nezami Ranjbar received his BSc and MSc in Electrical Engineering from Sharif University of Technology, Iran. He is currently a PhD student at Virginia Tech. His research interest is proteomics data modeling and analysis.
E-mail: email@example.com Office: 176 Building D Phone:202-687-1387
Yi Zhao, M.S. Research Assistant
Yi Zhao received her B.S. in statistics from School of Mathematical Sciences, Nankai University, China. She got her M.S. in biostatistics from Georgetown University, USA in 2012. Her research interest is non-parametric statistics and high-dimensional data.
E-mail: firstname.lastname@example.org Office: 174 Building D Phone:202-687-3045/202-687-7369
Minkun (Kevin) Wang, B.S. Research Assistant
Kevin (Minkun) Wang received his B.S. degree in Electrical Engineering from University of Science and Technology of China. He is currently a PhD candidate at Virginia Tech in Dept. ECE. His research interest is signal/image processing, sparse representation via dictionary learning, and machine learning methods for image processing.
E-mail: email@example.com Office: 176 Building D Phone:Phone: 202-687-9369/202-687-1387
Yiming (Mike) Zuo, B.S. Research Assistant
Yiming Zuo received his B.S. degree in the Information Science & Electronic Engineering from Zhejiang University, China in 2012. He is currently a Ph.D. student of Virginia Tech. He is a research assistant at Department of Oncology, Georgetown University. His research interest is developing methods for metabolic data processing.
E-mail: firstname.lastname@example.org Office: 176 Building D Phone: 202-687-3381
Yue Luo (Karen), M.S. Research Associate
Yue Luo (Karen) received her M.S. degree in analytical chemistry from University of Vermont, and her B.S. degree from Zhejiang University, China. Prior joining in Ressom Lab, she worked in Metabolomics Core Facility for two years. She is interested in applying mass spectrometry in metabolomics, lipidomics and proteomics research.
E-mail: email@example.com Office: W325 Research Building Phone:202-687-4453
- JunFeng Xiao, Ph.D.,received his PhD in Analytical Chemistry from Rensselaer Polytechnic Institute (RPI) in 2009. He is interested in applying mass spectrometry for both proteomics and metabolomics studies.
- Yuji Zhang, Ph.D., Virginia Tech (Currently Assistant Professor of Medical Informatics, Mayo Clinic, Rochester, MN )
Ph.D. Thesis (2005-10): "Module-based analysis of biological data for network inference and biomarker discovery"
- Leepika Tuli, Ph.D., Postdoctoral Research Fellow, Georgetown University
- Zhiqun Tang, Ph.D., Postdoctoral Research Fellow, Georgetown University
- Getachew K. Befekadu, Ph.D., Postdoctoral Research Fellow, Georgetown University
- Lanlan Yin, M.S., Georgetown University
- Kevin Turner, M.S., University of Maine
M.S. Thesis (2005-07): "Estimation of ocean water chlorophyll-a concentration using fuzzy c-means clustering and artificial neural networks"
- Mohamad Driss, M.S., University of Maine
M.S. Thesis (2002-05): "Nonlinear PCA based on radial basis function and particle swarm optimization"
- Kamal Shannak, M.S., University of Maine
M.S. Thesis (2002-04): "On nonlinear principal component analysis for process monitoring"
- Rency S. Varghese, M.S., University of Maine
M.S. Thesis (2002-04): "Confidence measure for DNA base calling using a fuzzy system"
- Siva Srirangam, M.S., University of Maine
M.S. Thesis (2002-04) "Retrieval of oceanic and physiological parameters using computational intelligence"
- Wayne H. Slade, Jr., M.S., University of Maine
M.S. Thesis (2001-04) "Computational intelligence approaches to ocean color inversion"
- Dali Wang, M.S., University of Maine
M.S. Thesis (2000-03): "Adaptive double self-organizing map for clustering gene expression data"
- Robert Reynolds, M.S., University of Maine
M.S. Thesis (2000-01): "Gene expression data analysis using fuzzy logic"
- Yuqing Zhang, High school intern
| ©2010-2013 Ressom Lab Suite 173, Building D 4000 Reservoir Rd,N.W., Washington, D.C. 20057-1484 || |