Publications

A Bayesian approach to determine the composition of heterogeneous cancer tissue

Published in BMC bioinformatics, 2018

In this paper, we propose an algorithm to tackle the challenge of determining the composition of a heterogeneous cancer tissue by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework.

Recommended citation: Ashish Katiyar, Anwoy Mohanty, Jianping Hua, Sima Chao, Rosana Lopes, Aniruddha Datta and Michael L. Bittner(2018). "A Bayesian approach to determine the composition of heterogeneous cancer tissue" BMC Bioinformatics. 2018;19(Suppl 3)1 https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-018-2062-0

Bayesian data and channel joint maximum-likelihood based error correction in wireless sensor networks

Published in Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief, 2011

The proposed algorithm employs the temporal correlation of the narrowband sensor data in conjunction with the channel state information (CSI) for detection and error correction of the data received over the Rayleigh fading wireless channel.

Recommended citation: Ashish Katiyar, and Aditya K. Jagannatham (2011) "Bayesian data and channel joint maximum-likelihood based error correction in wireless sensor networks" Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief pp 141-146 http://www.iitk.ac.in/mwn/papers/acwr2011_submission_ashish.pdf