CJ Barberan

435 total citations · 1 hit paper
4 papers, 204 citations indexed

About

CJ Barberan is a scholar working on Artificial Intelligence, Molecular Biology and Oncology. According to data from OpenAlex, CJ Barberan has authored 4 papers receiving a total of 204 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Molecular Biology and 1 paper in Oncology. Recurrent topics in CJ Barberan's work include AI in cancer detection (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). CJ Barberan is often cited by papers focused on AI in cancer detection (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). CJ Barberan collaborates with scholars based in United States and Brazil. CJ Barberan's co-authors include Richard G. Baraniuk, Advait Balaji, Todd J. Treangen, R. A. Leo Elworth, Chen Dun, Nicolae Sapoval, Ruth Dannenfelser, Luay Nakhleh, Zhi Yan and Dinler A. Antunes and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Computerized Medical Imaging and Graphics.

In The Last Decade

CJ Barberan

3 papers receiving 199 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.

Current progress and open challenges for applying deep learning across the biosciences

2022 171 citations Nicolae Sapoval, Amirali Aghazadeh et al. Nature Communications profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
CJ Barberan United States	3	135	43	18	16	14	4	204
C. Wolfe United States	4	124 0.9×	52 1.2×	11 0.6×	16 1.0×	14 1.0×	7	208
Anna Swan United Kingdom	3	152 1.1×	27 0.6×	15 0.8×	10 0.6×	15 1.1×	5	239
Theofanis Karaletsos United States	7	139 1.0×	51 1.2×	10 0.6×	9 0.6×	15 1.1×	16	223
Hassaan Maan Canada	7	314 2.3×	41 1.0×	28 1.6×	19 1.2×	52 3.7×	9	480
Euiseong Ko United States	5	215 1.6×	37 0.9×	32 1.8×	18 1.1×	48 3.4×	9	319
Farida Zehraoui France	10	191 1.4×	67 1.6×	17 0.9×	10 0.6×	59 4.2×	25	281
Armin Meier United Kingdom	7	93 0.7×	61 1.4×	79 4.4×	9 0.6×	18 1.3×	12	223
Jasper Zuallaert Belgium	7	134 1.0×	32 0.7×	49 2.7×	13 0.8×	10 0.7×	12	228
Binhua Tang China	7	185 1.4×	34 0.8×	16 0.9×	19 1.2×	50 3.6×	16	255

Countries citing papers authored by CJ Barberan

Since Specialization

Citations

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

Fields of papers citing papers by CJ Barberan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of CJ Barberan

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

All Works

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4 of 4 papers shown

1.

Sapoval, Nicolae, Amirali Aghazadeh, Michael Nute, et al.. (2022). Current progress and open challenges for applying deep learning across the biosciences. Nature Communications. 13(1). 1728–1728. 171 indexed citations breakdown →

2.

Barberan, CJ, Brady Hunt, Mila Pontremoli Salcedo, et al.. (2022). Multi-task network for automated analysis of high-resolution endomicroscopy images to detect cervical precancer and cancer. Computerized Medical Imaging and Graphics. 97. 102052–102052. 19 indexed citations

3.

Barberan, CJ, et al.. (2022). NeuroView-RNN: It’s About Time. 1683–1697.

4.

Elworth, R. A. Leo, Qi Wang, CJ Barberan, et al.. (2020). To Petabytes and beyond: recent advances in probabilistic and signal processing algorithms and their application to metagenomics. Nucleic Acids Research. 48(10). 5217–5234. 14 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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