Felix Agakov

3.8k citations
44 papers · 2.3k indexed · h-index 21

Impact in

Papers in

Felix Agakov

44 papers receiving 2.3k citations

Peers

Felix Agakov
Comparison fields: 5 of 167
  • Hardware and Architecture 499
  • Nephrology 199
  • Software 77
  • Artificial Intelligence 463
  • Genetics 391
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Citations per field
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Citations per year

Countries citing papers authored by Felix Agakov

Since Specialization
Citations

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

Fields of papers citing papers by Felix Agakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Felix Agakov, 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 Felix Agakov Line = papers co-authored together Felix Agakov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 202331
3 20222
4
Plasma N-glycans in colorectal cancer risk
20188
5 201852
6 201793
7 201617
8 2015124
9 201553
10
Discriminative Mixtures of Sparse Latent Fields for Risk Management
20125
11
Inference of Causal Relationships between Biomarkers and Outcomes in High Dimensions
20115
12 201174
13 2011353
14
Sparse Instrumental Variables (SPIV) for Genome-Wide Studies
20105
15
Kernel Multi-task Learning using Task-specific Features
200751
16
Code Generation and Optimization, 2007. CGO '07. International Symposium on
2007102
17
Kernelized Infomax Clustering
200517
18
Extreme Components Analysis
200314
19
Information Maximization in Noisy Channels : A Variational Approach
20034
20
Products of Gaussians
20019

About Felix Agakov

Felix Agakov is a scholar working on Hardware and Architecture, Signal Processing, Artificial Intelligence, Genetics and Nephrology, having authored 44 papers that have together received 2.3k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (5 papers), Genetic Mapping and Diversity in Plants and Animals (5 papers), Blind Source Separation Techniques (4 papers), Genetic Associations and Epidemiology (4 papers), Genetic and phenotypic traits in livestock (4 papers), Neural Networks and Applications (4 papers), Parallel Computing and Optimization Techniques (3 papers) and Galectins and Cancer Biology (3 papers). The work is most often cited by research in Hardware and Architecture (499 citations), Nephrology (199 citations), Software (77 citations), Artificial Intelligence (463 citations) and Genetics (391 citations). Felix Agakov has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Edwin V. Bonilla, Grigori Fursin, Igor Rudan, David Barber, Christopher K. I. Williams, Paul McKeigue, Michael O’Boyle, Evropi Τheodoratou, Lina Zgaga and John Cavazos. Their work appears in journals such as Scientific Reports, Lara D. Veeken, Diabetologia, PLoS ONE and Genetic Epidemiology.

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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