Biology subjects

Arora, R.

Publications and source records attributed to Arora, R..

57 records · Page 4Linked to original sources

bioRxiv2019

Repertoire-Based Diagnostics Using Statistical Biophysics

A fundamental challenge in immunology is diagnostic classification based on repertoire sequence. We used the principle of maximum entropy (MaxEnt) to build compact representations of antibody (IgH) and T-cell receptor (TCR{beta}) CDR3 repertoires based on the statistical biophysical patterns latent in the frequency and ordering of repertoires constituent amino acids. This approach results in substantial advantages in quality, dimensionality, and training speed compared to MaxEnt models based solely on the standard 20-letter amino-acid alphabet. Descriptor-based models learn patterns that pure amino-acid-based models cannot. We demonstrate the utility of descriptor models by successfully classifying influenza vaccination status (AUC=0.97, p=4x10-3), requiring only 31 samples from 14 individuals. Descriptor-based MaxEnt modeling is a powerful new method for dissecting, encoding, and classifying complex repertoires.

immunology↗

bioRxiv2018

Immunological Diversity with Similarity

A diverse immune repertoire is considered a hallmark of good health, but measuring diversity requires a framework that incorporates not only sequences relative frequencies but also their functional similarity to each other. Using experimentally measured dissociation constants from over 1,300 antibody-antigen and T-cell receptor (TCR)-peptide pairs, we developed a framework for functional immunological diversity based on binding and applied it to nearly 400 high-throughput antibody and TCR repertoires to reveal patterns in immunological memory, infection, vaccination, and aging. We show that functional diversity adds information that is not captured by raw diversity, revealing signatures of e.g. clonal selection, and that unlike raw diversity, functional diversity is a robust measure that does not require correction for sampling error. Finally, we show that according to functional diversity, unlike raw diversity, individuals repertoires overlap substantially, indicating a definable ceiling for the functional diversity of human adaptive immunity. Similarity redefines diversity in complex systems.

immunology↗

bioRxiv2017

Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data

Omics data contains signal from the molecular, physical, and kinetic inter- and intra-cellular interactions that control biological systems. Matrix factorization techniques can reveal low-dimensional structure from high-dimensional data that reflect these interactions. These techniques can uncover new biological knowledge from diverse high-throughput omics data in topics ranging from pathway discovery to time course analysis. We review exemplary applications of matrix factorization for systems-level analyses. We discuss appropriate application of these methods, their limitations, and focus on analysis of results to facilitate optimal biological interpretation. The inference of biologically relevant features with matrix factorization enables discovery from high-throughput data beyond the limits of current biological knowledge--answering questions from high-dimensional data that we have not yet thought to ask.

systems biology↗