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Laksshman Sundaram
Laksshman Sundaram
Graduate Student in Computer Science, Stanford University
Verified email at stanford.edu
Title
Cited by
Cited by
Year
Predicting the clinical impact of human mutation with deep neural networks
L Sundaram, H Gao, SR Padigepati, JF McRae, Y Li, JA Kosmicki, ...
Nature genetics 50 (8), 1161-1170, 2018
3552018
Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution
AE Trevino, F Müller, J Andersen, L Sundaram, A Kathiria, A Shcherbina, ...
Cell 184 (19), 5053-5069. e23, 2021
2222021
Deep Learning-Based Techniques for Training Deep Convolutional Neural Networks
H Gao, F Kai-How, L Sundaram, JF McRAE
US Patent App. 16/160,903, 2019
772019
Working toward precision medicine: Predicting phenotypes from exomes in the Critical Assessment of Genome Interpretation (CAGI) challenges
R Daneshjou, Y Wang, Y Bromberg, S Bovo, PL Martelli, G Babbi, ...
Human mutation 38 (9), 1182-1192, 2017
472017
Semantic edge labeling over legal citation graphs
A Sadeghian, L Sundaram, D Wang, W Hamilton, K Branting, C Pfeifer
Proceedings of the workshop on legal text, document, and corpus analytics …, 2016
46*2016
DeepBipolar: Identifying genomic mutations for bipolar disorder via deep learning
S Laksshman, RR Bhat, V Viswanath, X Li
Human mutation 38 (9), 1217-1224, 2017
432017
The landscape of tolerated genetic variation in humans and primates
H Gao, T Hamp, J Ede, JG Schraiber, J McRae, M Singer-Berk, Y Yang, ...
Science 380 (6648), eabn8153, 2023
422023
Semi-supervised learning for training an ensemble of deep convolutional neural networks
L Sundaram, F Kai-How, H Gao, JF McRAE
US Patent 11,798,650, 2023
412023
Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease
M Ameen, L Sundaram, M Shen, A Banerjee, S Kundu, S Nair, ...
Cell 185 (26), 4937-4953. e23, 2022
192022
Deep convolutional neural networks for variant classification
L Sundaram, F Kai-How, H Gao, SR PADIGEPATI, JF McRAE
US Patent 11,315,016, 2022
182022
Stepwise Generation of Human Induced Pluripotent Stem Cell–Derived Cardiac Pericytes to Model Coronary Microvascular Dysfunction
M Shen, C Liu, SR Zhao, A Manhas, L Sundaram, M Ameen, JC Wu
Circulation 147 (6), 515-518, 2023
62023
Identification of constrained sequence elements across 239 primate genomes
LFK Kuderna, JC Ulirsch, S Rashid, M Ameen, L Sundaram, G Hickey, ...
Nature 625 (7996), 735-742, 2024
42024
Transcription factor stoichiometry, motif affinity and syntax regulate single-cell chromatin dynamics during fibroblast reprogramming to pluripotency
S Nair, M Ameen, L Sundaram, A Pampari, J Schreiber, A Balsubramani, ...
bioRxiv, 2023
42023
Deep Learning-Based Techniques for Training Deep Convolutional Neural Networks
H Gao, F Kai-How, L Sundaram, JF McRAE
US Patent App. 16/773,678, 2020
42020
CAGI, the Critical Assessment of Genome Interpretation, establishes progress and prospects for computational genetic variant interpretation methods
N Null, S Jain, C Bakolitsa, SE Brenner, P Radivojac, J Moult, S Repo, ...
Genome Biology 25 (1), 1-46, 2024
12024
Critical assessment of genome interpretation consortium. CAGI, the critical assessment of genome interpretation, establishes progress and pprospects for computational genetic …
S Jain, C Bakolitsa, EB Steven, P Radivojac, J Moult, S Repo, AH Roger, ...
Genome Biology 22 (22; 25 (1): 53.), 1-46, 2024
2024
Quality detection of variant calling using a machine learning classifier
H Gao, H Tobias, JGJ McMaster-Schraiber, L Sundaram, F Kai-How
US Patent App. 17/952,194, 2023
2023
Variant calling without a target reference genome
H Gao, H Tobias, JGJ McMaster-Schraiber, L Sundaram, F Kai-How
US Patent App. 17/952,192, 2023
2023
Unique mapper tool for excluding regions without one-to-one mapping between a set of two reference genomes
H Gao, H Tobias, JGJ McMaster-Schraiber, L Sundaram, F Kai-How
US Patent App. 17/952,198, 2023
2023
Deep learning-based use of protein contact maps for variant pathogenicity prediction
C Chen, H Gao, LS Sundaram, F Kai-How
US Patent App. 17/876,501, 2023
2023
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