Minghua Deng

Molecular Biology · 2002–2018

A researcher in the Science corpus: 6 papers; trusts 20 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 53 citations into it; #10,850 of 17,773 by trust here, #8,280 by citations
• Computational Biology & Bioinformatics — 12 citations into it
• Artificial Intelligence — 9 citations into it
• Materials Chemistry — 7 citations into it
• Model Architectures — 5 citations into it

Whom Minghua Deng trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Tim Hesterberg
2. D. Lockhart
3. Joel R. Bock
4. Paul Pavlidis
5. Sheng Wang
6. Haretsugu Hishigaki
7. Jason Aaron Edward Weston
8. Michael S. Brown
9. Elizabeth A. Winzeler
10. William Noble Grundy

Who trusts Minghua Deng overall

1. Benjamin A. Shoemaker
2. Roded Sharan
3. Reedik Mägi
4. Anna R. Panchenko
5. Jeffrey D. Wall
6. Igor Ulitsky
7. Rina Foygel Barber
8. Asa Ben-Hur
9. Yanjun Qi

Papers from Minghua Deng's perspective

Ordered by how strongly the researchers Minghua Deng trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Going deeper with convolutions
3. Rectified Linear Units Improve Restricted Boltzmann Machines
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning (2018) — 44 citations
• Inferring domain-domain interactions from protein-protein interactions (2002) — 475 citations
• Prediction of Protein Function Using Protein–Protein Interaction Data (2002) — 387 citations
• Kernel-Based Data Fusion and Its Application to Protein Function Prediction in Yeast (2003) — 354 citations
• A dynamic programming algorithm for haplotype block partitioning (2002) — 366 citations
• Stochastic model of yeast cell-cycle network (2006) — 90 citations