(7am) Leveraging Big Data and Engineering Fundamentals Towards Rational Biological Discovery | AIChE

(7am) Leveraging Big Data and Engineering Fundamentals Towards Rational Biological Discovery

Authors 

Dixit, P. - Presenter, Columbia University
Research Interests:

Advances in -omics technologies now allow researchers to quickly collect large amounts of diverse information about biological systems. The descriptive models in quantitative biology, which are inspired by this big data avalanche, need to be complemented with a mechanistic understanding of the underlying biological processes through integration of the -omics data with physical and physiological constraints that govern biological systems.

My future research in systems biology will pursue two distinct directions: (I) Gaining mechanistic insights into cell-to-cell variability in mammalian cellular signaling net- works in order to understand its role in important biological functions such as emergence of chemotherapy resistant tumor cells and (II) Identifying the forces that shape bacterial genome evolution with a goal of exploring how bacterial phenotypic traits are innovated and spread in natural populations.

Teaching Interests:

My academic and research training has spanned many fundamental areas of chemical engineering. As a result, I am very comfortable teaching core subjects such as thermodynamics, transport phenomena, chemical kinetics, and process control and optimization. Additionally, my postdoctoral training allows me to teach many non-traditional electives. I would be interested in teaching the following electives:

Molecular modeling of biomolecules: The junior/senior level course will be divided in three sections and will be heavily based on projects. The initial third of the course will cover operational basics of thermodynamics, statistical mechanics, classical mechanics, and quantum chemistry. In the next section, a brief introduction will be given to free energy calculations and to the popular software. In the last section, students will carry out exercises in molecular simulations including simple liquid systems, spin systems, and proteins. These exercises will be designed as small research problems which if successfully completed may result in publications in peer reviewed journals.

Systems biophysics: Complex biological systems are organized in networks of interacting elements; for example, gene regulatory network, protein interaction network, metabolic network, etc. We are continuously updating our understanding of how these networks have evolved and how they operate. It is becoming clear that basic physical can have highly non-trivial effects on the fate of biological networks. Given our progress over the last decade, there have been multiple books explaining the organization of biological networks and the role of physical and physiological constraints in shaping those networks. Drawing examples from my research experience, I would like to teach a seminar course to show students the key experimental and theoretical discoveries in our understanding of dynamics, organization, and evolution of biological networks in recent years. This course will aim to show how biophysics and biochemistry have shaped evolution of networks of proteins, organisms, and ecologies.

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