Selected Publications

Selected Journal Publications:

P. Rajdeo, B. Aronow, V. B. S. Prasath. Deep learning-based multimodal spatial transcriptomics analysis for cancer. Advances in Cancer Research, 163, July 2024. doi:10.1016/bs.acr.2024.08.001. Full Text 

R. Nakagaki, S. S. Debsarkar, H. Kawanaka, B. Aronow, V. B. S. Prasath. Deep learning-based IDH1 gene mutation prediction using histopathological imaging and clinical data. Computers in Biology and Medicine, 179, 108902, September 2024. doi:10.1016/j.compbiomed.2024.108902

X. Liu, S. Prasath, I. Siddiqui, T. Walters, L. A Denson, PROTECT consortium, J. Dhaliwal. Machine learning-based prediction of pediatric ulcerative colitis treatment response using diagnostic histopathology. Gastroenterology, 166(5), 921-924, May 2024. doi:10.1053/j.gastro.2024.01.033

X. Liu, J. Reigle, V. B. S. Prasath, J. Dhaliwal. Artificial intelligence image-based prediction models in IBD exhibit high risk of bias: A systematic review. Computers in Biology and Medicine, 171, 108093, March 2024. doi:10.1016/j.compbiomed.2024.108093

E. G. Zarajabad, P. D. Grimm, B. Saremi, J. Wang, S. A. Ahmad, S. A. Shah, R. C. Quillin III, S. H. Patel, A. J. Knapp, V. B. S. Prasath, T. D. Mast. Deep learning-enhanced 3D echo decorrelation imaging for monitoring radiofrequency ablation in ex vivo human liver. Proceedings of Meetings on Acoustics (POMA), 51(1), February 2024. doi:10.1121/2.0001821

LungMAP flow

N. Gaddis, J. Fortriede, M. Guo, E. E. Bardes, M. Kouril, S. Tabar, K. Burns, M. E. Ardini-Poleske, S. Loos, D. Schnell, K. Jin, B. Iyer, Y. Du, B.-X. Huo, A. Bhattacharjee, J. Korte, R. Munshi, V. Smith, A. Herbst, J. A. Kitzmiller, G. C. Clair, J. Carson, J. Adkins, E. E. Morrisey, G. S. Pryhuber, R. Misra, J. A. Whitsett, X. Sun, T. Heathorn, B. Paten, V. B. S. Prasath, Y. Xu, T. Tickle, B. J. Aronow, N. Salomonis. LungMAP portal ecosystem: Systems-level exploration of the lung. American Journal of Respiratory Cell and Molecular Biology, 129-139, 70(2), February 2024. doi:10.1165/rcmb.2022-0165OC

P.-J. Van Camp, V. B. S. Prasath, D. B. Haslam, A. Porallo. MGS2AMR: A gene-centric mining of metagenomic sequencing data for pathogens and their antimicrobial resistance profile. Microbiome, 11, Article number 223, October 2023. doi:10.1186/s40168-023-01674-z (Github)

T. A Cazares, F. W. Rizvi, B. Iyer, X. Chen, M. Kotliar, J. A. Wayman, A. Bejjani, O. Donmez, B. Wronowski, S. Parameswaran, L. C. Kottyan, A. Barski, M. T. Weirauch, V. B. S. Prasath, E. R. Miraldi. maxATAC: genome-scale transcription-factor binding prediction from ATAC-seq with deep neural networks. PLOS Computational Biology, 19(1), e1010863, January 2023. doi:10.1371/journal.pcbi.1010863 

(Github, PyPI)

G. Li, B. Song, H. Singh, V. B. S. Prasath, H. L. Grimes, N. Salomonis. Decision level integration of unimodal and multimodal single cell data with scTriangulate. Nature Communications, 14, 406, January 2023. doi:10.1038/s41467-023-36016-y (Github, PyPI)

M. Shah, D. Jain, V. B. S. Prasath, K. Dufendach. Artificial intelligence in bronchopulmonary dysplasia - Current research and unexplored frontiers. Pediatric Research, 93(2), 287-290, January 2023. doi:10.1038/s41390-022-02387-z

K. Jin, D. Schnell, G. Li, N. Salomonis, S. Prasath, R. Szczesniak, B. J. Aronow. CellDrift: Inferring perturbation responses in temporally sampled single-cell data. Briefings in Bioinformatics, 23(5), September 2022. doi:10.1093/bib/bbac324

(Github)

G. Li, B. Iyer, V. B. S. Prasath, Y. Ni, N. Salomonis. DeepImmuno: Deep learning-empowered prediction and generation of immunogenic peptides for T-cell immunity. Briefings in Bioinformatics, 22(6), 1-16, November 2021. doi:10.1093/bib/bbab160 (ScienceBlog, Featured-Research, Portal, Github)

M. Shah, D. Shu, V. B. S. Prasath, Y. Ni, A. Schapiro, K. Dufendach. Machine learning for detection of correct peripherally inserted central catheter tip position from radiology reports in infants. Applied Clinical Informatics, 12(04), 856-863, August 2021. doi:10.1055/s-0041-1735178

Nature Paper Figure

J. Zhang, Q. Wu, C. B. Johnson, G. Pham, J. M. Kinder, A. Olsson, A. Slaughter, M. May, B. Weinhaus, A. D'Alessandro, J. D. Engel, J. X. Jiang, J. M. Kofron, L. F. Huang, V. B. S. Prasath, S. S. Way, N. Salomonis, H. L. Grimes, D. Lucas. In situ mapping identifies distinct vascular niches for myelopoiesis. Nature, 590, 457-462, February 2021. doi:10.1038/s41586-021-03201-2 (Euerkalert, ScienceMag)

T. Hayakawa, V. B. S. Prasath, H. Kawanaka, B. J. Aronow, S. Tsuruoka. Computational nuclei segmentation methods in digital pathology - A survey. Archives of Computational Methods in Engineering, 28(1), 1-13, January 2021. doi:10.1007/s11831-019-09366-4

D. N. H. Thanh, V. B. S. Prasath, L. M. Hieu, N. N. Hien. Melanoma skin cancer detection method based on adaptive principal curvature, colour normalisation and feature extraction with the ABCD rule. Journal of Digital Imaging, 33(3), 574-585, June 2020. doi:10.1007/s10278-019-00316-x

H. A. A. Alfeilat, A. B. A. Hassanat, O. Lasassmeh, A. S. Tarawneh, M. B. Alhasanat, H. S. E. Salman, V. B. S. Prasath. Effects of distance measure choice on KNN classifier performance - A review. Big Data, 7(4), 221-248, December 2019. doi:10.1089/big.2018.0175

V. B. S. Prasath, R. Pelapur, G. Seetharaman, K. Palaniappan. Multiscale structure tensor for improved feature extraction and image regularization. IEEE Transactions on Image Processing, 28(12), 6198-6210, December 2019. doi:10.1109/TIP.2019.2924799

A. Yonekura, H. Kawanaka, V. B. S. Prasath, B. J. Aronow, H. Takase. Automatic disease stage classification of glioblastoma multiforme histopathological images using deep convolutional neural network. Biomedical Engineering Letters, 8(3), 321-327, August 2018. doi:10.1007/s13534-018-0077-0

Selected Conference Publications:


Full list of Conference Publications