Frank Emmert‐Streib

8.5k citations
248 papers · 5.4k indexed · 2 hit papers · h-index 38
Topics
Bioinformatics and Genomic Networks (79 papers)Gene expression and cancer classification (55 papers)Gene Regulatory Network Analysis (50 papers)
Journals
Nucleic Acids ResearchSHILAP Revista de lepidopterologíaBioinformatics

In The Last Decade

Frank Emmert‐Streib

234 papers receiving 5.3k citations

Hit Papers

An Introductory Review of Deep Learning for Prediction Mo...202020262022202420202024100200300

Peers

Frank Emmert‐Streib
Comparison fields: 5 of 215
  • Molecular Biology 2.4k
  • Computational Theory and Mathematics 1.1k
  • Artificial Intelligence 853
  • Geometry and Topology 610
  • Statistical and Nonlinear Physics 567
Replace Matthias Dehmer with:
Matthias Dehmer Austria
Robert L. Grossman United States
Reinhard Laubenbacher United States
Shuigeng Zhou China
Nataša Pržulj United Kingdom
Jihong Guan China
Shai Ben-David Israel
Jia Liu China
Xian Wu China
Mauricio Barahona United Kingdom
Frank Emmert‐Streib relative to Matthias Dehmer Austria Matthias Dehmer's profile →
Citations per field
00.5×1.5×1.8×
Matthias Dehmer · 1×
Citations per year

Countries citing papers authored by Frank Emmert‐Streib

Since Specialization
Citations

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

Fields of papers citing papers by Frank Emmert‐Streib

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank Emmert‐Streib. 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 Frank Emmert‐Streib. The network helps show where Frank Emmert‐Streib may publish in the future.

Co-authorship network of co-authors of Frank Emmert‐Streib

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Emmert‐Streib. A scholar is included among the top collaborators of Frank Emmert‐Streib 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 Frank Emmert‐Streib. Frank Emmert‐Streib 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 2
2 4
3 7
4 145
5 50
6 16
7 49
8 15
9 13
10 2
11 2
12 6
13 5
14 37
15 4
16 96
17 9
18
Theoretical Bounds for the Number of Inferable Edges in Sparse Random Networks.
1
19
Active Learning in Recurrent Neural Networks Facilitated by a Hebb-like Learning Rule with Memory
3
20
A stochastic model for the estimation of perceptual switching events in pigeons
2

About Frank Emmert‐Streib

Frank Emmert‐Streib is a scholar working on Geometry and Topology, Statistical and Nonlinear Physics and Computational Theory and Mathematics, having authored 248 papers that have together received 5.4k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (79 papers), Gene expression and cancer classification (55 papers) and Gene Regulatory Network Analysis (50 papers). The work is most often cited by research in Geometry and Topology (610 citations), Health Informatics (93 citations) and Computational Theory and Mathematics (1.1k citations). Frank Emmert‐Streib has collaborated with scholars based in Austria, Finland and United States. Frequent co-authors include Matthias Dehmer, Galina Glazko, Shailesh Tripathi, Gökmen Altay, Ricardo De Matos Simoes, Olli Yli‐Harja, Benjamin Haibe‐Kains, Yongtang Shi, Zhen Yang and Feng Han. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

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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