Vision

Our vision is to advance our understanding and make sense of big data in life and health sciences through developing and applying integrative informatics tools and methodologies to enable and accelerate translational science.

Methodology

In realizing our vision, we will form data science teams and participate in several interdisciplinary research projects. Our methodology employs machine learning and system biology approaches to address emerging data integration challenges (e.g., heterogeneity, scalability,...

About us

Welcome to the Integrative Data Science Research (IDSR) group founded by Dr. Yasser El-Manzalawy. The primary goal of IDSR is to develop innovative algorithms and tools for enabling and promoting data-intensive, collaborative, and translational research in precision medicine, microbiome research, and health/clinical informatics.

Research areas

Multi-view and privileged learning
Multi-view and privileged learning
  Our methodology for addressing the data integration challenges is mainly based on two recent advances in machine learning research: i) multi-view learning; ii) learning...
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Structural Bioinformatics
Structural Bioinformatics
  A common theme of Yasser's research in the area of bioinformatics is the development and the application of state-of-the-art machine learning algorithms to decipher...
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Health Informatics
Health Informatics
Wearable mHealth devices are being used in a variety of healthcare scenarios including tracking of sleep and physical activities. mHealth technology is a promising direction...
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Metagenomics
Metagenomics
Metagenome-wide analysis studies provide a unique set of microbial features for biomarker discovery of associated disease as well as for studying diversity and dynamics of...
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Translational Bioinformatics
Translational Bioinformatics
Large-scale collaborative precision medicine initiatives (e.g., The Cancer Genome Atlas (TCGA)) are yielding rich multi-omics data. Integrative analyses of the resulting multi-omics data offer the...
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Software

Dr. El-Manzalawy has developed, implemented, and is maintaining the following free accessibly web servers and open source libraries:

Proxi: a Python package for proximity graph construction
  Graph-based representation of metagenomic data is a promising direction not only...
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Gennotate
Gennotate: a platform for sharing data representations, predictors, and machine learning algorithms...
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Epitopes Toolkit (EpiT)
Epitopes Toolkit (EpiT) is a platform for developing epitope prediction tools. An...
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WLSVM
Weka LibSVM (WLSVM): Integrating LibSVM into Weka Environment Weka and LibSVM are...
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Bioinformatics web servers
  Vaccine Informatics BCPREDS: B-cell epitope prediction MHCMIR: Predicting MHC-II peptide binding...
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