Mikhail Markovsky

Molecular Biology · 2019

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 27 citations into it
• Computational Biology & Bioinformatics — 17 citations into it
• Materials Chemistry — 15 citations into it

Whom Mikhail Markovsky trusts overall

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

1. Sargur N. Srihari
2. Alec Radford
3. Moustafa Farid Alzantot
4. Carol A. Rohl
5. Pehr Harbury
6. Robbie P. Joosten
7. Michael D. Tyka
8. Wouter G. Touw
9. Peter J. A. Cock

Who trusts Mikhail Markovsky overall

1. Kevin E. Wu

Papers from Mikhail Markovsky's perspective

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

1. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
2. Biopython: freely available Python tools for computational molecular biology and bioinformatics
3. Mixture Density Networks
4. The Rosetta all-atom energy function for macromolecular modeling and design
5. A series of PDB related databases for everyday needs
6. Protein Structure Prediction Using Rosetta
7. Alternate states of proteins revealed by detailed energy landscape mapping
8. SenseGen: A deep learning architecture for synthetic sensor data generation
9. Directed evolution: new parts and optimized function
10. High-resolution protein design with backbone freedom.

Their papers

• RamaNet: Computational de novo helical protein backbone design using a long short-term memory generative neural network (2019) — 24 citations