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Reconstructing cell cycle and disease progression using deep learning

Nature communications, 2017-09, Vol.8 (1), p.463-6, Article 463

2017

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Hierarchical graph learning for protein-protein interaction

Nature communications, 2023-02, Vol.14 (1), p.1093-1093, Article 1093

2023

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Neuroinspired unsupervised learning and pruning with subquantum CBRAM arrays

Nature communications, 2018-12, Vol.9 (1), p.5312-11, Article 5312

2018

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Improved protein structure refinement guided by deep learning based accuracy estimation

Nature communications, 2021-02, Vol.12 (1), p.1340-1340, Article 1340

2021

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MolDiscovery: learning mass spectrometry fragmentation of small molecules

Nature communications, 2021-06, Vol.12 (1), p.3718-3718, Article 3718

2021

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Humans monitor learning progress in curiosity-driven exploration

Nature communications, 2021-10, Vol.12 (1), p.5972-5972, Article 5972

2021

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Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning

Nature communications, 2021-05, Vol.12 (1), p.3238-3238, Article 3238

2021

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Deep learning-assisted comparative analysis of animal trajectories with DeepHL

Nature communications, 2020-10, Vol.11 (1), p.5316-5316, Article 5316

2020

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A versatile active learning workflow for optimization of genetic and metabolic networks

Nature communications, 2022-07, Vol.13 (1), p.3876-3876, Article 3876

2022

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Clearing Opacity Through Machine Learning

Iowa law review, 2021-01, Vol.106 (2), p.775-812

2021

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Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets

Nature communications, 2021-05, Vol.12 (1), p.3023-3023, Article 3023

2021

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Machine Learning as Natural Monopoly

Iowa law review, 2022-05, Vol.107 (4), p.1543-1614

Narechania, Tejas N

2022

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Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation

Nature communications, 2020-12, Vol.11 (1), p.6254-6254, Article 6254

2020

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Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

Nature communications, 2023-03, Vol.14 (1), p.1679-1679, Article 1679

2023

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Neural alignment predicts learning outcomes in students taking an introduction to computer science course

Nature communications, 2021-03, Vol.12 (1), p.1922-1922, Article 1922

2021

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Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning

Nature communications, 2021-04, Vol.12 (1), p.2302-2302, Article 2302

2021

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Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation

Nature communications, 2023-09, Vol.14 (1), p.5792-5792, Article 5792

2023

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Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures

Nature communications, 2023-10, Vol.14 (1), p.6564-6564, Article 6564

2023

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3D-integrated multilayered physical reservoir array for learning and forecasting time-series information

Nature communications, 2024-03, Vol.15 (1), p.2044-2044, Article 2044

2024

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Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

Breast cancer research : BCR, 2024-05, Vol.26 (1), p.82-82

2024

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A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet

BMC cancer, 2023-11, Vol.23 (1), p.1-1060, Article 1060

2023

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Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

BMC cancer, 2024-03, Vol.24 (1), p.315-315

2024

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G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma

BMC cancer, 2024-01, Vol.24 (1), p.157-157, Article 157

2024

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Object recognition in rats and mice: a one-trial non-matching-to-sample learning task to study 'recognition memory'

Nature protocols, 2006-10, Vol.1 (3), p.1306-1311

2006

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Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma

BMC cancer, 2024-03, Vol.24 (1), p.363-363

2024

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Reconstructing cell cycle and disease progression using deep learning

Hierarchical graph learning for protein-protein interaction

Neuroinspired unsupervised learning and pruning with subquantum CBRAM arrays

Improved protein structure refinement guided by deep learning based accuracy estimation

MolDiscovery: learning mass spectrometry fragmentation of small molecules

Humans monitor learning progress in curiosity-driven exploration

Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning

Deep learning-assisted comparative analysis of animal trajectories with DeepHL

A versatile active learning workflow for optimization of genetic and metabolic networks

Clearing Opacity Through Machine Learning

Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets

Machine Learning as Natural Monopoly

Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation

Deep learning-enabled segmentation of ambiguous bioimages with deepflash2

Neural alignment predicts learning outcomes in students taking an introduction to computer science course

Detecting protein and DNA/RNA structures in cryo-EM maps of intermediate resolution using deep learning

Seasonal pigment fluctuation in diploid and polyploid Arabidopsis revealed by machine learning-based phenotyping method PlantServation

Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures

3D-integrated multilayered physical reservoir array for learning and forecasting time-series information

Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study

A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

G6PD and machine learning algorithms as prognostic and diagnostic indicators of liver hepatocellular carcinoma

Object recognition in rats and mice: a one-trial non-matching-to-sample learning task to study 'recognition memory'

Research on multi-model imaging machine learning for distinguishing early hepatocellular carcinoma

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