Soma Kobayashi

1.4k total citations
8 papers, 124 citations indexed

About

Soma Kobayashi is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, Soma Kobayashi has authored 8 papers receiving a total of 124 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Oncology. Recurrent topics in Soma Kobayashi's work include Inflammatory Bowel Disease (2 papers), Single-cell and spatial transcriptomics (2 papers) and Colorectal Cancer Screening and Detection (2 papers). Soma Kobayashi is often cited by papers focused on Inflammatory Bowel Disease (2 papers), Single-cell and spatial transcriptomics (2 papers) and Colorectal Cancer Screening and Detection (2 papers). Soma Kobayashi collaborates with scholars based in United States and Spain. Soma Kobayashi's co-authors include Joel Saltz, Vincent W. Yang, Miriam Mérad, Yonit Lavin, Felipe Were, Rajarsi Gupta, Tahsin Kurç, María Casanova-Acebes, Luke A. Torre-Healy and Alina M. Hamilton and has published in prestigious journals such as Nature Communications, Gastroenterology and PLoS ONE.

In The Last Decade

Soma Kobayashi

8 papers receiving 124 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Soma Kobayashi United States	5	47	41	38	24	23	8	124
Khalid AbdulJabbar United Kingdom	7	36 0.8×	37 0.9×	41 1.1×	23 1.0×	21 0.9×	9	112
Arthur Lewis United Kingdom	6	71 1.5×	71 1.7×	35 0.9×	21 0.9×	22 1.0×	9	197
Cédric Balsat Belgium	8	28 0.6×	67 1.6×	109 2.9×	37 1.5×	37 1.6×	9	212
Karma Dacosta United States	6	85 1.8×	29 0.7×	99 2.6×	19 0.8×	13 0.6×	13	157
Wuliang Wang China	8	28 0.6×	68 1.7×	47 1.2×	17 0.7×	53 2.3×	28	201
Jill S. Frank United States	8	29 0.6×	75 1.8×	102 2.7×	10 0.4×	38 1.7×	14	150
Cody N. Heiser United States	7	45 1.0×	143 3.5×	60 1.6×	17 0.7×	39 1.7×	13	241
Daiwei Zhang United States	6	29 0.6×	129 3.1×	24 0.6×	12 0.5×	38 1.7×	8	212
Carolien Duetz Netherlands	6	21 0.4×	43 1.0×	22 0.6×	10 0.4×	8 0.3×	15	133
Mateo Sokač Denmark	6	24 0.5×	36 0.9×	43 1.1×	40 1.7×	28 1.2×	18	150

Countries citing papers authored by Soma Kobayashi

Since Specialization

Citations

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

Fields of papers citing papers by Soma Kobayashi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soma Kobayashi

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

All Works

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8 of 8 papers shown

1.

Kobayashi, Soma, Christopher J. Sullivan, Agnieszka B. Bialkowska, Joel Saltz, & Vincent W. Yang. (2023). Computational immunohistochemical mapping adds immune context to histological phenotypes in mouse models of colitis. Scientific Reports. 13(1). 14386–14386. 1 indexed citations

2.

Fassler, Danielle, Luke A. Torre-Healy, Rajarsi Gupta, et al.. (2022). Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression. Cancers. 14(9). 2148–2148. 36 indexed citations

3.

Kobayashi, Soma, Yang Liu, Prateek Prasanna, et al.. (2022). Deep learning-based approach to the characterization and quantification of histopathology in mouse models of colitis. PLoS ONE. 17(8). e0268954–e0268954. 4 indexed citations

4.

Chu, Timothy, Yang Liu, Soma Kobayashi, et al.. (2022). KLF5 protects the intestinal epithelium against Th17 immune response in a murine colitis model. JCI Insight. 7(7). 12 indexed citations

5.

Kobayashi, Soma, Joel Saltz, & Vincent W. Yang. (2021). State of machine and deep learning in histopathological applications in digestive diseases. World Journal of Gastroenterology. 27(20). 2545–2575. 14 indexed citations

6.

Kobayashi, Soma, et al.. (2021). Fr619 DEEP LEARNING CLASSIFIER TO DETECT INFLAMED AND NON-INFLAMED AREAS WITHIN WHOLE MOUSE COLONS.. Gastroenterology. 160(6). S–379. 1 indexed citations

7.

Casanova-Acebes, María, María Piedad Menéndez-Gutierrez, Damiana Álvarez‐Errico, et al.. (2020). RXRs control serous macrophage neonatal expansion and identity and contribute to ovarian cancer progression. Nature Communications. 11(1). 1655–1655. 46 indexed citations

8.

Rahman, Adeeb, Yonit Lavin, Soma Kobayashi, Andrew M. Leader, & Miriam Mérad. (2017). High‐dimensional single cell mapping of cerium distribution in the lung immune microenvironment of an active smoker. Cytometry Part B Clinical Cytometry. 94(6). 941–945. 10 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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