Artem Sokolov

9.6k citations
53 papers · 1.6k indexed · 2 hit papers · h-index 17
Topics
Topic Modeling (17 papers)Natural Language Processing Techniques (16 papers)Bioinformatics and Genomic Networks (7 papers)

In The Last Decade

Artem Sokolov

50 papers receiving 1.5k citations

Hit Papers

N-Myc Drives Neuroendocrine Prostate Cancer Initiated fro...20162026201920222016202150100150200250

Peers

Artem Sokolov
Comparison fields: 5 of 129
  • Molecular Biology 817
  • Pulmonary and Respiratory Medicine 488
  • Cancer Research 317
  • Oncology 240
  • Artificial Intelligence 219
Replace Laura M. Heiser with:
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Artem Sokolov relative to Laura M. Heiser United States Laura M. Heiser's profile →
Citations per field
00.5×1.5×2.5×
Laura M. Heiser · 1×
Citations per year

Countries citing papers authored by Artem Sokolov

Since Specialization
Citations

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

Fields of papers citing papers by Artem Sokolov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Artem Sokolov

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2 2
3 8
4 5
5 24
6 41
7
Machine learning identifies candidates for drug repurposing in Alzheimer’s diseasebreakdown →
181
8 26
9 3
10 6
11 1
12
Bandit Structured Prediction for Learning from Partial Feedback in Statistical Machine Translation
4
13
N-Myc Drives Neuroendocrine Prostate Cancer Initiated from Human Prostate Epithelial Cellsbreakdown →
280
14 74
15
Coactive learning for interactive machine translation
2
16 214
17 48
18
The HDU Discriminative SMT System for Constrained Data PatentMT at NTCIR10
0
19
LIMSI @ WMT12
9
20
LIMSI: Learning Semantic Similarity by Selecting Random Word Subsets
5

About Artem Sokolov

Artem Sokolov is a scholar working on Artificial Intelligence, Biophysics and Computational Theory and Mathematics, having authored 53 papers that have together received 1.6k indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Natural Language Processing Techniques (16 papers) and Bioinformatics and Genomic Networks (7 papers). The work is most often cited by research in Cancer Research (317 citations), Pulmonary and Respiratory Medicine (488 citations) and Molecular Biology (817 citations). Artem Sokolov has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Joshua M. Stuart, Robert Baertsch, Asa Ben‐Hur, Evan Paull, Owen N. Witte, B. Smith, Colleen Mathis, Donghui Cheng, Darrell Whitley and Kiley Graim. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

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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