Alexis Lamiable

1.2k total citations · 1 hit paper
10 papers, 855 citations indexed

About

Alexis Lamiable is a scholar working on Molecular Biology, Biophysics and Artificial Intelligence. According to data from OpenAlex, Alexis Lamiable has authored 10 papers receiving a total of 855 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Biophysics and 1 paper in Artificial Intelligence. Recurrent topics in Alexis Lamiable's work include RNA and protein synthesis mechanisms (5 papers), Protein Structure and Dynamics (4 papers) and Chemical Synthesis and Analysis (3 papers). Alexis Lamiable is often cited by papers focused on RNA and protein synthesis mechanisms (5 papers), Protein Structure and Dynamics (4 papers) and Chemical Synthesis and Analysis (3 papers). Alexis Lamiable collaborates with scholars based in France, United States and Lebanon. Alexis Lamiable's co-authors include Pierre Tufféry, P. Thévenet, Julien Rey, Philippe Derreumaux, Isabelle Callebaut, Tristan Bitard‐Feildel, J.-P. Mornon, Dominique Barth, Sandrine Vial and Alain Denise and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Alexis Lamiable

9 papers receiving 846 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.

PEP-FOLD3: fasterde novostructure prediction for linear peptides in solution and in complex

2016 759 citations Alexis Lamiable, P. Thévenet et al. Nucleic Acids Research profile →

Peers

Alexis Lamiable

MB

MICRO

IMMUN

RNMI

ID

Sumeet Patiyal India

Alexis Musacchio Cuba

Nishant Thakur India

Con Dogovski Australia

Shion A. Lim United States

Nicolas Sapay France

Piyush Agrawal India

Shilpa R. Shenoy United States

Salman Sadullah Usmani India

Sumeet Patiyal India

Alexis Lamiable

713 ×1.1

MB

129 ×0.7

MICRO

135 ×1.1

IMMUN

108 ×1.1

RNMI

109 ×1.2

ID

Citations per year, relative to Alexis Lamiable Alexis Lamiable (= 1×) peers Sumeet Patiyal

Countries citing papers authored by Alexis Lamiable

Since Specialization

Citations

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

Fields of papers citing papers by Alexis Lamiable

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexis Lamiable

This figure shows the co-authorship network connecting the top 25 collaborators of Alexis Lamiable. A scholar is included among the top collaborators of Alexis Lamiable 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 Alexis Lamiable. Alexis Lamiable is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Bardes, Adrien, et al.. (2024). Exploring self-supervised learning biases for microscopy image representation. SHILAP Revista de lepidopterología. 4. e12–e12.

2.

Lamiable, Alexis, Peter Sommer, Nicolas Argy, et al.. (2023). Revealing invisible cell phenotypes with conditional generative modeling. Nature Communications. 14(1). 6386–6386. 13 indexed citations

3.

Lamiable, Alexis, Tristan Bitard‐Feildel, Joseph Rebehmed, et al.. (2019). A topology-based investigation of protein interaction sites using Hydrophobic Cluster Analysis. Biochimie. 167. 68–80. 11 indexed citations

4.

Faure, Guilhem, et al.. (2019). Discovery and Evolution of New Domains in Yeast Heterochromatin Factor Sir4 and Its Partner Esc1. Genome Biology and Evolution. 11(2). 572–585. 7 indexed citations

5.

Bitard‐Feildel, Tristan, Alexis Lamiable, J.-P. Mornon, & Isabelle Callebaut. (2018). Order in Disorder as Observed by the “Hydrophobic Cluster Analysis” of Protein Sequences. PROTEOMICS. 18(21-22). e1800054–e1800054. 25 indexed citations

6.

Lamiable, Alexis, et al.. (2017). Peptide Suboptimal Conformation Sampling for the Prediction of Protein-Peptide Interactions. Methods in molecular biology. 21–34. 1 indexed citations

7.

Lamiable, Alexis, et al.. (2016). PEP-FOLD3: fasterde novostructure prediction for linear peptides in solution and in complex. Nucleic Acids Research. 44(W1). W449–W454. 759 indexed citations breakdown →

8.

Lamiable, Alexis, P. Thévenet, & Pierre Tufféry. (2016). A critical assessment of hidden markov model sub‐optimal sampling strategies applied to the generation of peptide 3D models. Journal of Computational Chemistry. 37(21). 2006–2016. 10 indexed citations

9.

Lamiable, Alexis, et al.. (2013). An Algorithmic Game-Theory Approach for Coarse-Grain Prediction of RNA 3D Structure. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(1). 193–199. 11 indexed citations

10.

Lamiable, Alexis, et al.. (2012). Automated prediction of three-way junction topological families in RNA secondary structures. Computational Biology and Chemistry. 37. 1–5. 18 indexed citations

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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