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Jyotasana Gulati
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Jyotasana Gulati


Summary

Bioinformatics Scientist at Alkahest.
PostDoctoral research from Max Planck Institute of Chemical Ecology.
Ph.D. from International Max Planck Research School.

Research Areas: Developing statistical and machine learning methods to analyze pre-clinical and clinical data sets, high throughput genomic data analysis, Biomedical informatics, Natural language processing for biomarker discovery, informatics for therapeutics development.

Bioinformatics Data Mining & Machine Learning Data Science Ecology Genomics Neuroscience Plant Science Statistics

Work details

Scientist

Alkahest Inc.
November 2016
Bioinformatics
I am working as Bioinformatics Scientist and my research

Research Scientist (IMPRS Research Fellowship)

Max Planck Institute for Chemical Ecology
January 2010 - December 2013
• Applied pattern recognition methods on big biological Omics datasets (time course experiment) using R and Python. • Designed statistical framework using multivariate techniques to characterize dynamics of activation in time and space of gene-metabolite pool. • Studied and reported biologically significant emergent properties of features extracted from a multifactorial data set.

Postdoctoral Research Scientist

Max Planck Institute of Chemical Ecology
January 2014 - April 2016
• Analyzed time-series dataset for classification/regression, clustering and predictive modelling problems using R and Python. • Classified proteins, genes and metabolites using circadian time series analyses obtained from a cross-sectional time course microarray experiments. • Predicted rhythmicity and its alteration in silenced lines using single time point microarray experiments. • Analyzed complex networks of altered biological pathways in silenced circadian clock components. • Developed web interfaces using d3.js (Javascript library) to display weather field data to help scientist design their experiments.

Websites

  • Google Scholar
  • LinkedIn