J. Schaarschmidt

Molecular Biology · 2017

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom J. Schaarschmidt trusts overall

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

  1. Sheng Wang
  2. Christophe Nicolas Magnan
  3. Siqi Sun
  4. Kira M. S. Misura
  5. Pierre Baldi
  6. David T. Jones
  7. Jinbo Xu
  8. Johannes Söding
  9. Daniel W. A. Buchan
  10. Dylan Chivian

Who trusts J. Schaarschmidt overall

  1. Duccio Malinverni
  2. Andriy Kryshtafovych
  3. Mu Gao
  4. Lisa N. Kinch
  5. John Moult
  6. Yang Liu
  7. Rojan Shrestha
  8. Hong Zeng
  9. Krzysztof Fidelis
  10. Alessandro Barducci

Papers from J. Schaarschmidt's perspective

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

  1. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model
  2. SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity
  3. Analysis of deep learning methods for blind protein contact prediction in CASP12
  4. Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules
  5. Improved protein contact predictions with the MetaPSICOV2 server in CASP12
  6. Sequence co-evolution gives 3D contacts and structures of protein complexes
  7. Identification of direct residue contacts in protein–protein interaction by message passing
  8. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
  9. Physically realistic homology models built with ROSETTA can be more accurate than their templates.
  10. ImageNet classification with deep convolutional neural networks

Their papers