Martin Weigt

10.3k total citations · 4 hit papers
103 papers, 6.1k citations indexed

About

Martin Weigt is a scholar working on Molecular Biology, Condensed Matter Physics and Genetics. According to data from OpenAlex, Martin Weigt has authored 103 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Molecular Biology, 19 papers in Condensed Matter Physics and 16 papers in Genetics. Recurrent topics in Martin Weigt's work include Protein Structure and Dynamics (27 papers), RNA and protein synthesis mechanisms (23 papers) and Bioinformatics and Genomic Networks (23 papers). Martin Weigt is often cited by papers focused on Protein Structure and Dynamics (27 papers), RNA and protein synthesis mechanisms (23 papers) and Bioinformatics and Genomic Networks (23 papers). Martin Weigt collaborates with scholars based in France, Italy and Germany. Martin Weigt's co-authors include Terence Hwa, Alain Barrat, Hendrik Szurmant, Alexander K. Hartmann, Andrea Pagnani, Riccardo Zecchina, José N. Onuchic, James A. Hoch, Faruck Morcos and Robert A. White and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Martin Weigt

98 papers receiving 6.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Direct-coupling analysis of residue coevolution captures native contacts across many protein families

2011 971 citations Faruck Morcos, Andrea Pagnani et al. Proceedings of the National Academy of Sciences profile →
Identification of direct residue contacts in protein–protein interaction by message passing

2008 695 citations Martin Weigt, Robert A. White et al. Proceedings of the National Academy of Sciences profile →
On the properties of small-world network models

2000 553 citations Martin Weigt et al. profile →
Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models

2013 438 citations Martin Weigt et al. profile →

Peers

Countries citing papers authored by Martin Weigt

Since Specialization

Citations

This map shows the geographic impact of Martin Weigt's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Martin Weigt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Weigt more than expected).

Fields of papers citing papers by Martin Weigt

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Weigt. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Martin Weigt. The network helps show where Martin Weigt may publish in the future.

Co-authorship network of co-authors of Martin Weigt

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Weigt. A scholar is included among the top collaborators of Martin Weigt based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Martin Weigt. Martin Weigt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	TULIP: A transformer-based unsupervised language model for interacting peptides and T cell receptors that generalizes to unseen epitopes 2024 ·Proceedings of the National Academy of Sciences ·(unknown), Christoph Feinauer, Martin Weigt, Aleksandra M. Walczak, Thierry Mora	20
2	Towards parsimonious generative modeling of RNA families 2024 ·Nucleic Acids Research ·(unknown), (unknown), Philippe Nghe, Francesco Zamponi, Martin Weigt	5
3	Generating interacting protein sequences using domain-to-domain translation 2023 ·Bioinformatics ·(unknown), (unknown), Martin Weigt, Andrea Pagnani, Christoph Feinauer	3
4	Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins 2023 ·PLoS Computational Biology ·(unknown), (unknown), Anne‐Florence Bitbol, Martin Weigt	4
5	Epistatic models predict mutable sites in SARS-CoV-2 proteins and epitopes 2022 ·Proceedings of the National Academy of Sciences ·Juan Rodriguez-Rivas, Giancarlo Croce, Maureen Muscat, Martin Weigt	50
6	Modeling Sequence-Space Exploration and Emergence of Epistatic Signals in Protein Evolution 2022 ·IRIS Research product catalog (Sapienza University of Rome) ·(unknown), Juan Rodriguez-Rivas, Francesco Zamponi, Martin Weigt	26
7	On the effect of phylogenetic correlations in coevolution-based contact prediction in proteins 2021 ·PLoS Computational Biology ·(unknown), Martin Weigt	15
8	Efficient generative modeling of protein sequences using simple autoregressive models 2021 ·Nature Communications ·(unknown), Guido Uguzzoni, Andrea Pagnani, Francesco Zamponi, Martin Weigt	54
9	An evolution-based model for designing chorismate mutase enzymes 2020 ·Science ·William P. Russ, Matteo Figliuzzi, Christian Stocker, Pierre Barrat-Charlaix, Michael Socolich, Peter Kast, Donald Hilvert, Rémi Monasson, Simona Cocco, Martin Weigt, Rama Ranganathan	166
10	Aligning biological sequences by exploiting residue conservation and coevolution 2020 ·Physical review. E ·(unknown), Andrea Pagnani, Martin Weigt, Francesco Zamponi	9
11	Toward Inferring Potts Models for Phylogenetically Correlated Sequence Data 2019 ·Entropy ·(unknown), Pierre Barrat-Charlaix, Martin Weigt	13
12	Phylogenetic correlations can suffice to infer protein partners from sequences 2019 ·PLoS Computational Biology ·(unknown), Martin Weigt, Anne‐Florence Bitbol	19
13	Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis 2017 ·Proceedings of the National Academy of Sciences ·Guido Uguzzoni, (unknown), Francesco Oteri, Alexander Schug, Hendrik Szurmant, Martin Weigt	65
14	Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis 2016 ·Proceedings of the National Academy of Sciences ·Thomas Gueudré, Carlo Baldassi, Marco Zamparo, Martin Weigt, Andrea Pagnani	75
15	Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon 2016 ·PLoS ONE ·Christoph Feinauer, Hendrik Szurmant, Martin Weigt, Andrea Pagnani	34
16	Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis 2012 ·Proceedings of the National Academy of Sciences ·Angel E. Dago, Alexander Schug, Andrea Procaccini, James A. Hoch, Martin Weigt, Hendrik Szurmant	110
17	Estimation of Residue-Residue Coevolution using Direct Coupling Analysis Identifies Many Native Contacts Across a Large Number of Domain Families 2012 ·Biophysical Journal ·Faruck Morcos, (unknown), Bryan Lunt, (unknown), Debora S. Marks, Chris Sander, Riccardo Zecchina, José N. Onuchic, Terence Hwa, Martin Weigt	2
18	Identification of direct residue contacts in protein–protein interaction by message passing breakdown → 2008 ·Proceedings of the National Academy of Sciences ·Martin Weigt, Robert A. White, Hendrik Szurmant, James A. Hoch, Terence Hwa	695
19	Statistical mechanics perspective on the phase transition in vertex covering of finite-connectivity random graphs 2001 ·Theoretical Computer Science ·Alexander K. Hartmann, Martin Weigt	17
20	The typical-case complexity of a vertex-covering algorithm on finite-connectivity random graphs 2000 ·arXiv (Cornell University) ·Martin Weigt, Alexander K. Hartmann	4

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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