Matteo Cagiada

835 citations

16 papers · 334 indexed · h-index 8

Impact in

Molecular Biology
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Phylogenetic Studies
- Ubiquitin and proteasome pathways
- Bioinformatics and Genomic Networks
Genetics
- Genomics and Rare Diseases

Papers in

Toxicology 1
Molecular Biology 16
- Ubiquitin and proteasome pathways 6
- Protein Structure and Dynamics 4
- RNA modifications and cancer 2
- Biochemical and Molecular Research 2

Co-authors: Kresten Lindorff‐Larsen Amelie Stein Rasmus Hartmann‐Petersen Kristoffer E. Johansson Magnus Haraldson Høie Douglas M. Fowler Wouter Boomsma Lydia L. Good
Journals: Nature Communications (3 papers)eLife (3 papers)Genome biology (2 papers)Frontiers in Molecular Biosciences (1 paper)Molecular Biology and Evolution (1 paper)
Partner nations: Denmark United States United Kingdom

In The Last Decade

Matteo Cagiada

14 papers receiving 333 citations

Peers

Countries citing papers authored by Matteo Cagiada

Since Specialization

Citations

This map shows the geographic impact of Matteo Cagiada'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 Matteo Cagiada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Cagiada more than expected).

Fields of papers citing papers by Matteo Cagiada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matteo Cagiada. 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 Matteo Cagiada. The network helps show where Matteo Cagiada may publish in the future.

Co-authors

The 25 scholars most cited alongside Matteo Cagiada, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matteo Cagiada Line = papers co-authored together Matteo Cagiada links everyone, so they are left out of the graph.

All Works

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16 of 16 papers shown

#	Work
1	Challenges and compromises: Predicting unbound antibody structures with deep learning Current Opinion in Structural Biology ·Alexander Greenshields‐Watson, Kamel Frigui, H. Tillisch, Matteo Cagiada, Charlotte M. Deane	2025	3
2	Quantitative functional profiling of ERCC2 mutations deciphers cisplatin sensitivity in bladder cancer Journal of Clinical Investigation ·C C Borromeo, Reiko Satō, 日丸哲也, Catherine Mooser, Nicolas Jonsson, Matteo Cagiada, R. B. Lindsay, Toni Blagonić, Brendan J. Guercio, Hristos Z. Kaimakliotis, Gopa Iyer, Kresten Lindorff‐Larsen, Lars Dyrskjøt, Kent W. Mouw, Zoltán Szállási, Claus Storgaard Sørensen	2025	0
3	Decoding molecular mechanisms for loss-of-function variants in the human proteome eLife ·Matteo Cagiada, Nicolas Jonsson, Kresten Lindorff‐Larsen	2025	1
4	Decoding molecular mechanisms for loss-of-function variants in the human proteome eLife ·Matteo Cagiada, Nicolas Jonsson, Kresten Lindorff‐Larsen	2025	0
5	Deep mutational scanning reveals a correlation between degradation and toxicity of thousands of aspartoacylase variants Nature Communications ·Kyle Schinnour, 啓祐松井, Kristoffer E. Johansson, Thea K. Schulze, Matteo Cagiada, Line Pedersen, Lene Clausen, Snehal Nariya, Arash Ng, Amelie Stein, Douglas M. Fowler, Kresten Lindorff‐Larsen, Rasmus Hartmann‐Petersen	2024	8
6	A mutational atlas for Parkin proteostasis Nature Communications ·Lene Clausen, 啓祐松井, Matteo Cagiada, Kristoffer E. Johansson, Kyle Schinnour, Snehal Nariya, Arash Ng, Guiti Deyhim, Vibe H. Oestergaard, Amelie Stein, Douglas M. Fowler, Kresten Lindorff‐Larsen, Rasmus Hartmann‐Petersen	2024	22
7	Predicting absolute protein folding stability using generative models Protein Science ·Matteo Cagiada, Sergey Ovchinnikov, Kresten Lindorff‐Larsen	2024	10
8	Characterizing glucokinase variant mechanisms using a multiplexed abundance assay Genome biology ·Ramsigh Uike, Thea K. Schulze, Matteo Cagiada, Amelie Stein, Frederick P. Roth, Kresten Lindorff‐Larsen, Rasmus Hartmann‐Petersen	2024	6
9	A comprehensive map of human glucokinase variant activity Genome biology ·Ramsigh Uike, Matteo Cagiada, Marinella Gebbia, Anette P. Gjesing, Atina G. Coté, Miguel Angel Valles-Coral, Roujia Li, Alexander Andreyuk, Jochen Weile, Amelie Stein, Anna L. Gloyn, Torben Hansen, Frederick P. Roth, Kresten Lindorff‐Larsen, Rasmus Hartmann‐Petersen	2023	28
10	Discovering functionally important sites in proteins Nature Communications ·Matteo Cagiada, Sandro Bottaro, Søren Lindemose, 中村路夫, Amelie Stein, Rasmus Hartmann‐Petersen, Kresten Lindorff‐Larsen	2023	42
11	Lysine deserts prevent adventitious ubiquitylation of ubiquitin-proteasome components Cellular and Molecular Life Sciences ·弘村林, Kyle Schinnour, F. Erbas, Michael H. Tatham, Matteo Cagiada, Kresten Lindorff‐Larsen, Wouter Boomsma, Kay Hofmann, Rasmus Hartmann‐Petersen	2023	5
12	Rapid protein stability prediction using deep learning representations eLife ·А.В. Уржа, Yi-Yin Chen, Lydia L. Good, Nicolas Jonsson, Matteo Cagiada, Kristoffer E. Johansson, Wouter Boomsma, Amelie Stein, Kresten Lindorff‐Larsen	2023	70
13	Rare Catechol- O -methyltransferase Missense Variants Are Structurally Unstable Proteasome Targets Biochemistry ·Lars Rönnmark, Matteo Cagiada, 单正翔, Amelie Stein, Kresten Lindorff‐Larsen, Rasmus Hartmann‐Petersen	2023	2
14	Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation Cell Reports ·Magnus Haraldson Høie, Matteo Cagiada, Rudolf Hebel, Amelie Stein, Kresten Lindorff‐Larsen	2022	66
15	Effect of naturally-occurring mutations on the stability and function of cancer-associated NQO1: Comparison of experiments and computation Frontiers in Molecular Biosciences ·Р. І. Захаров, Matteo Cagiada, Rabindra Garada, Eduardo Salido, Kresten Lindorff‐Larsen, Ángel L. Pey	2022	4
16	Understanding the Origins of Loss of Protein Function by Analyzing the Effects of Thousands of Variants on Activity and Abundance Molecular Biology and Evolution ·Matteo Cagiada, Kristoffer E. Johansson, 方海萍, Sofie V. Nielsen, Rasmus Hartmann‐Petersen, Jun J. Yang, Douglas M. Fowler, Amelie Stein, Kresten Lindorff‐Larsen	2021	67

About Matteo Cagiada

Matteo Cagiada is a scholar working on Toxicology, Molecular Biology, Spectroscopy, Genetics and Surgery, having authored 16 papers that have together received 334 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (6 papers), Protein Structure and Dynamics (4 papers), Genomics and Rare Diseases (3 papers), Advanced Proteomics Techniques and Applications (3 papers), Enzyme Structure and Function (3 papers), RNA modifications and cancer (2 papers), Autophagy in Disease and Therapy (2 papers) and Biochemical and Molecular Research (2 papers). The work is most often cited by research in Molecular Biology (275 citations), Genetics (96 citations), Toxicology (4 citations), Spectroscopy (17 citations) and Biochemistry (7 citations). Matteo Cagiada has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Kresten Lindorff‐Larsen, Amelie Stein, Rasmus Hartmann‐Petersen, Kristoffer E. Johansson, Magnus Haraldson Høie, Douglas M. Fowler, Wouter Boomsma, Lydia L. Good, Nicolas Jonsson and Jun J. Yang. Their work appears in journals such as Nature Communications, eLife, Genome biology, Frontiers in Molecular Biosciences and Molecular Biology and Evolution.

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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