W. Sheffler
Molecular Biology · 2007–2026
A researcher in the Science corpus: 25 papers; trusts 22 researchers and is trusted by 34 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 403 citations into it; #1,268 of 17,773 by trust here, #695 by citations
- Materials Chemistry — 231 citations into it; #1,655 of 11,513 by trust here, #2,915 by citations
- Computational Biology & Bioinformatics — 106 citations into it; #594 of 660 by trust here, #125 by citations
- Artificial Intelligence — 17 citations into it
Whom W. Sheffler trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Carol A. Rohl
- Alex Smola
- David Baker
- Bernhard E. Boser
- Vladimir Naumovich Vapni
- Adam T. Zemla
- Charles E.M. Strauss
- Peter L. Bartlett
- Isabelle M Guyon
- Vladimir Naumovich Vapnik
Who trusts W. Sheffler overall
- Michael Jendrusch
- Paul D. Adams
- Namrata Anand-Achim
- Sarel Jacob Fleishman
- Raphael R. Eguchi
- P. Benjamin Stranges
- Namrata Anand
- I. Korendovych
- Gideon Lapidoth
- Randy J. Read
Papers from W. Sheffler's perspective
Ordered by how strongly the researchers W. Sheffler trusts endorse each paper. Same corpus, a different order for every researcher.
- The Nature of Statistical Learning Theory
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- A training algorithm for optimal margin classifiers
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Long Short-Term Memory
Their papers
- Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules (2011) — 1,780 citations
- Structure prediction for CASP8 with all-atom refinement using Rosetta (2009) — 496 citations
- Structure prediction for CASP7 targets using extensive all‐atom refinement with Rosetta@home (2007) — 222 citations
- RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation (2008) — 140 citations
- Computational design of self-assembling protein nanomaterials with atomic level accuracy (2012) — 628 citations
- Ranking predicted protein structures with support vector regression (2007) — 98 citations
- Accurate design of coassembling multi-component protein nanomaterials (2014) — 518 citations
- A New Generation of Crystallographic Validation Tools for the Protein Data Bank (2011) — 445 citations
- De novo design of a fluorescence-activating β-barrel (2018) — 312 citations
- Computational Design of Self-Assembling Cyclic Protein Homo-oligomers (2016) — 137 citations
- Broadly applicable and accurate protein design by integrating structure prediction networks and diffusion generative models (2022) — 200 citations
- Corrigendum: Design of a hyperstable 60-subunit protein icosahedron (2016) — 45 citations
- Accurate design of megadalton-scale two-component icosahedral protein complexes (2016) — 524 citations
- Design of a hyperstable 60-subunit protein icosahedron (2016) — 410 citations
- Tailored design of protein nanoparticle scaffolds for multivalent presentation of viral glycoprotein antigens (2020) — 147 citations
- Design of protein-binding proteins from the target structure alone (2022) — 514 citations
- Accurate computational design of multipass transmembrane proteins (2018) — 159 citations
- De novo design of protein structure and function with RFdiffusion (2023) — 1,299 citations
- Efficient Flexible Backbone Protein-Protein Docking for Challenging Targets (2017) — 158 citations
- Computational design of trimeric influenza neutralizing proteins targeting the hemagglutinin receptor binding site (2017) — 122 citations