Mona Singh

Computational Biology & Bioinformatics · 2005

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computational Biology & Bioinformatics — 12 citations into it
• Molecular Biology — 12 citations into it; #4,427 of 17,773 by trust here, #17,476 by citations
• Materials Chemistry — 6 citations into it

Whom Mona Singh trusts overall

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

1. Yuhai Wu
2. Pehr Harbury
3. Burkhard Rost
4. David C. Jones
5. James A. Cuff
6. Terrence J. Sejnowski
7. David E. Rumelhart
8. C. Burges
9. Manfred J. Sippl
10. George V. Cybenko

Who trusts Mona Singh overall

1. Ke Chen
2. Jian Zhou
3. Lukasz Kurgan
4. Olga G. Troyanskaya

Papers from Mona Singh's perspective

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

1. Predicting the secondary structure of globular proteins using neural network models.
2. Statistical Learning Theory
3. High-resolution protein design with backbone freedom.
4. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning representations by back-propagating errors
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Prediction of protein secondary structure at better than 70% accuracy.
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• Predicting Protein Secondary and Supersecondary Structure (2005) — 21 citations