Palukuri and Saleh


1) Predicting Human Protein Complexes Linked to SARS-COV2 with Super.Complex v3.0, and Multifidelity Importance Sampling for Gravitational Wave Inference and 2) Multifidelity Importance Sampling for Gravitational Wave Inference
Friday, March 26, 2021
2PM – 3PM
Zoom Meeting

1) Meghana Palukuri and 2) Bassel Saleh

Speaker 1: Meghana Palukuri. Protein complexes in an organism are groups of proteins that interact with each other to perform a particular function. These can be computationally predicted from a protein-interaction network using community detection algorithms. We predict 146 protein complexes potentially linked to SARS-COV2 that can be analyzed further to yield possible drug target sites and reveal insights into the mechanism of viral infection. These are a part of 1028 human protein complexes predicted from hu.MAP, a protein-interaction network with ~7k proteins (nodes) and ~15k interactions (edges) with our algorithm, Super.Complex v3.0, in an order of minutes on TACC’s Stampede2. We also briefly discuss future ideas including a reinforcement learning method for community detection and methods to further improve community embeddings.

Meghana Palukuri is a fourth-year Ph.D. student in the CSEM program, working with Dr. Edward Marcotte. Meghana holds undergraduate and masters degrees in chemical engineering from the Indian Institute of Technology Madras and has industrial experience through internships with Amazon and Schlumberger.

Speaker 2: Bassel Saleh. In this work we aim to solve the Bayesian inverse problem in gravitational wave analysis in a multifidelity framework. Recent developments in the theory of multifidelity modeling for many-query problems demonstrate the potential for accelerating the solution of such problems by combining evaluations of multiple models of varying accuracies and costs. We apply this methodology to the broad and diverse class of models used for simulating gravitational wave signals, focusing on multifidelity importance sampling methods that sample temperized low-fidelity posteriors in order to estimate statistics of an expensive high-fidelity posterior.

Bassel Saleh is a third-year PhD student in Dr. Omar Ghattas' research group. Bassel studied at UT Austin for his undergraduate degree in physics and computer science. He enjoys research that involves mathematically interesting models and conceptually challenging physics.

(The CSEM Student Forum is a seminar series given by current CSEM graduate students to their peers. The aim of the forum is to expose students to each other's research, encourage collaboration, and provide opportunities to practice presentation skills. First- and second-year CSEM students receive seminar credit for attending.)

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Hosted by Shane McQuarrie

 Live Zoom Meeting Link: Click Here to Watch