Christoffer H Norn

Molecular Biology · 2013–2023

A researcher in the Science corpus: 9 papers; trusts 11 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 439 citations into it; #11,912 of 17,773 by trust here, #4,614 by citations
• Materials Chemistry — 200 citations into it
• Computational Biology & Bioinformatics — 76 citations into it
• Computational Theory and Mathematics — 66 citations into it
• Spectroscopy — 40 citations into it
• Atomic and Molecular Physics, and Optics — 9 citations into it

Whom Christoffer H Norn trusts overall

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

1. David Baker
2. Jorge Cortés
3. Andrew Leaver-Fay
4. Sarel Jacob Fleishman
5. Paul Labute
6. Adrian A. Canutescu
7. Ivan V. Anishchenko
8. Po-Ssu Huang
9. Carol A. Rohl
10. Jianyi Yang

Who trusts Christoffer H Norn overall

1. Kevin Kaichuang Yang
2. Michael Jendrusch
3. Lewis Moffat
4. Jue Wang
5. Gideon Lapidoth
6. Zhenyu Yang
7. Jeffrey A. Ruffolo
8. J. Trinquier
9. Namrata Anand
10. Ivan V. Anishchenko

Papers from Christoffer H Norn's perspective

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

1. Alternate states of proteins revealed by detailed energy landscape mapping
2. Protein Structure Prediction Using Rosetta
3. RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation
4. Rosetta3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules
5. The Rosetta all-atom energy function for macromolecular modeling and design
6. Highly accurate protein structure prediction with AlphaFold
7. Modeling T cell receptor recognition of CD1-lipid and MR1-metabolite complexes
8. T-Cell Transfer Therapy Targeting Mutant KRAS in Cancer
9. Systematic Comparison of Amber and Rosetta Energy Functions for Protein Structure Evaluation.
10. Repurposing Citizen Science Games as Software Tools for Professional Scientists

Their papers

• De novo protein design by deep network hallucination (2020) — 559 citations
• Protein sequence design by conformational landscape optimization (2021) — 142 citations
• Macromolecular modeling and design in Rosetta: recent methods and frameworks (2020) — 783 citations
• AbDesign: an algorithm for combinatorial backbone design guided by natural conformations and sequences (2015) — 118 citations
• Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors (2013) — 39 citations
• Principles for computational design of binding antibodies (2017) — 136 citations
• High-accuracy modeling of antibody structures by a search for minimum-energy recombination of backbone fragments (2016) — 25 citations
• Computational design of protein self-assembly. (2016) — 53 citations
• De novo design of luciferases using deep learning (2023) — 377 citations