Jules Samaran

1.3k citations
6 papers · 619 · 2 hit papers · h-index 4

Impact in

Papers in

    • Single-cell and spatial transcriptomics 4
    • Bioinformatics and Genomic Networks 2
    • Gene Regulatory Network Analysis 1
    • Extracellular vesicles in disease 1

Jules Samaran

6 papers receiving 614 citations

Jules Samaran's Hit Papers

A Python library for probabilistic analysis of single-cell omics data 2022 · 399 citations
3990+1+3Years since publication100200300

Peers

Jules Samaran
Comparison fields: 5 of 78
  • Biophysics 62
  • Signal Processing 93
  • Immunology 101
  • Artificial Intelligence 169
  • Molecular Biology 288
Replace Michał Bereta with:
Michał Bereta Poland
Zichuan Liu China
Brandon Wang United States
Eric M. Kernfeld United States
Laura Cantini France
Il‐Youp Kwak South Korea
Xiaodong Cai United States
Thomas A. Geddes Australia
Jules Samaran relative to Michał Bereta Poland Michał Bereta's profile →
Citations per field
00.5×20×40×60×77×
Michał Bereta · 1×
Citations per year

Countries citing papers authored by Jules Samaran

Since Specialization
Citations

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

Fields of papers citing papers by Jules Samaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Jules Samaran, 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 Jules Samaran Line = papers co-authored together Jules Samaran links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown

About Jules Samaran

Jules Samaran is a scholar working on Biophysics, Molecular Biology, Signal Processing, Artificial Intelligence and Immunology, having authored 6 papers that have together received 619 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (4 papers), Bioinformatics and Genomic Networks (2 papers), Network Security and Intrusion Detection (1 paper), Gene Regulatory Network Analysis (1 paper), Anomaly Detection Techniques and Applications (1 paper), Extracellular vesicles in disease (1 paper), Time Series Analysis and Forecasting (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Biophysics (62 citations), Signal Processing (93 citations), Immunology (101 citations), Artificial Intelligence (169 citations) and Molecular Biology (288 citations). Jules Samaran has collaborated with scholars based in France, Germany and Singapore. Frequent co-authors include Wenyu Zhang, Savitha Ramasamy, Chuan-Sheng Foo, Laura Cantini, Gabriel Peyré, Jérémie Kalfon, Mayu Otani, Noa García, Chenhui Chu and Yuta Nakashima. Their work appears in journals such as Nature Communications, Nature Methods, Nature Biotechnology and IEEE Transactions on Neural Networks and Learning Systems.

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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