Petar V. Todorov

580 citations
10 papers · 286 indexed · 1 hit paper · h-index 7
Topics
Genetic Associations and Epidemiology (2 papers)DNA and Nucleic Acid Chemistry (2 papers)Computational Drug Discovery Methods (2 papers)

In The Last Decade

Petar V. Todorov

10 papers receiving 284 citations

Hit Papers

Machine learning identifies candidates for drug repurposi...2021202620222024202150100150

Peers

Petar V. Todorov
Comparison fields: 5 of 69
  • Molecular Biology 132
  • Computational Theory and Mathematics 91
  • Physiology 54
  • Pharmacology 42
  • Genetics 18
Replace Kyle E. Evans with:
Kyle E. Evans United States
George Zhou United States
Nienke Moret United States
Jielin Xu United States
Prafulla Tiwari India
Jill Steidl‐Nichols United States
Mirjam Brackhan Germany
Elena L. Cáceres United States
Dingzhou Li United States
Petar V. Todorov relative to Kyle E. Evans United States Kyle E. Evans's profile →
Citations per field
00.5×2.6×
Kyle E. Evans · 1×
Citations per year

Countries citing papers authored by Petar V. Todorov

Since Specialization
Citations

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

Fields of papers citing papers by Petar V. Todorov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Petar V. Todorov. 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 Petar V. Todorov. The network helps show where Petar V. Todorov may publish in the future.

Co-authorship network of co-authors of Petar V. Todorov

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 1
2 27
3 1
4
Machine learning identifies candidates for drug repurposing in Alzheimer’s diseasebreakdown →
181
5 18
6 6
7 12
8 21
9 17
10 2

About Petar V. Todorov

Petar V. Todorov is a scholar working on Endocrine and Autonomic Systems, Modeling and Simulation and Gastroenterology, having authored 10 papers that have together received 286 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (2 papers), DNA and Nucleic Acid Chemistry (2 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Health Informatics (10 citations), Computational Theory and Mathematics (91 citations) and Biological Psychiatry (8 citations). Petar V. Todorov has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include Peter K. Sorger, Steve Rodriguez, George Zhou, Bradley T. Hyman, Nienke Moret, Clemens B. Hug, Nathan Johnson, Mark W. Albers, Kyle E. Evans and Artem Sokolov. Their work appears in journals such as Nature Communications, Bioinformatics and Diabetes.

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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