István Miklós

1.4k total citations
34 papers, 792 citations indexed

About

István Miklós is a scholar working on Molecular Biology, Immunology and Computer Vision and Pattern Recognition. According to data from OpenAlex, István Miklós has authored 34 papers receiving a total of 792 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Immunology and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in István Miklós's work include Genomics and Phylogenetic Studies (9 papers), Immunotherapy and Immune Responses (7 papers) and Cancer Immunotherapy and Biomarkers (5 papers). István Miklós is often cited by papers focused on Genomics and Phylogenetic Studies (9 papers), Immunotherapy and Immune Responses (7 papers) and Cancer Immunotherapy and Biomarkers (5 papers). István Miklós collaborates with scholars based in Hungary, United States and United Kingdom. István Miklós's co-authors include János Podani, Aaron E. Darling, Mark A. Ragan, Péter L. Erdős, Irmtraud M. Meyer, Zoltán Toroczkai, Adam M. Novak, Jotun Hein, Rune B. Lyngsø and Lajos Soukup and has published in prestigious journals such as Journal of Clinical Oncology, Bioinformatics and PLoS ONE.

In The Last Decade

István Miklós

32 papers receiving 770 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
István Miklós Hungary 12 330 168 146 141 141 34 792
Willem Talloen Belgium 24 627 1.9× 277 1.6× 136 0.9× 147 1.0× 57 0.4× 79 1.9k
Jarad Niemi United States 15 232 0.7× 69 0.4× 57 0.4× 99 0.7× 166 1.2× 43 839
Christian Mazza Switzerland 14 352 1.1× 122 0.7× 42 0.3× 76 0.5× 63 0.4× 44 925
Catherine Larédo France 12 216 0.7× 141 0.8× 38 0.3× 111 0.8× 114 0.8× 36 737
Christoph Leuenberger Switzerland 12 193 0.6× 542 3.2× 90 0.6× 197 1.4× 67 0.5× 22 1.0k
Martin Gardner United Kingdom 16 369 1.1× 241 1.4× 172 1.2× 95 0.7× 320 2.3× 43 1.2k
Robert D. Edwards United States 14 122 0.4× 104 0.6× 102 0.7× 115 0.8× 76 0.5× 38 677
Francesc Rosselló Spain 15 553 1.7× 303 1.8× 63 0.4× 29 0.2× 278 2.0× 67 1.0k
Antonio Carvajal‐Rodríguez Spain 19 293 0.9× 508 3.0× 93 0.6× 226 1.6× 62 0.4× 54 1.2k
Christina A. Cobbold United Kingdom 15 113 0.3× 170 1.0× 173 1.2× 186 1.3× 69 0.5× 37 933

Countries citing papers authored by István Miklós

Since Specialization
Citations

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

Fields of papers citing papers by István Miklós

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of István Miklós

This figure shows the co-authorship network connecting the top 25 collaborators of István Miklós. A scholar is included among the top collaborators of István Miklós 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 István Miklós. István Miklós 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
1.
Erdős, Péter L., István Miklós, & Lajos Soukup. (2024). Fully graphic degree sequences and P-stable degree sequences. Advances in Applied Mathematics. 163. 102805–102805.
2.
Miklós, István, et al.. (2023). A Markov chain on the solution space of edge colorings of bipartite graphs. Discrete Applied Mathematics. 332. 7–22. 2 indexed citations
3.
Tóth, József, et al.. (2021). In Silico Model Estimates the Clinical Trial Outcome of Cancer Vaccines. Cells. 10(11). 3048–3048. 5 indexed citations
4.
Erdős, Péter L., et al.. (2021). The mixing time of switch Markov chains: A unified approach. European Journal of Combinatorics. 99. 103421–103421. 8 indexed citations
5.
Somogyi, E, et al.. (2021). A Peptide Vaccine Candidate Tailored to Individuals' Genetics Mimics the Multi-Targeted T Cell Immunity of COVID-19 Convalescent Subjects. Frontiers in Genetics. 12. 684152–684152. 12 indexed citations
6.
Erdős, Péter L., et al.. (2018). Efficiently sampling the realizations of bounded, irregular degree sequences of bipartite and directed graphs. PLoS ONE. 13(8). e0201995–e0201995. 5 indexed citations
7.
Herman, Joseph L., et al.. (2015). Efficient representation of uncertainty in multiple sequence alignments using directed acyclic graphs. BMC Bioinformatics. 16(1). 108–108. 11 indexed citations
8.
Erdős, Péter L., Sándor Z. Kiss, István Miklós, & Lajos Soukup. (2015). Approximate Counting of Graphical Realizations. PLoS ONE. 10(7). e0131300–e0131300. 8 indexed citations
9.
Czabarka, Éva, Aaron Dutle, Péter L. Erdős, & István Miklós. (2014). On realizations of a joint degree matrix. Discrete Applied Mathematics. 181. 283–288. 13 indexed citations
10.
Miklós, István, Péter L. Erdős, & Lajos Soukup. (2013). Towards Random Uniform Sampling of Bipartite Graphs with given Degree Sequence. The Electronic Journal of Combinatorics. 20(1). 16 indexed citations
11.
Miklós, István & Zoltán Zádori. (2012). Positive Evolutionary Selection of an HD Motif on Alzheimer Precursor Protein Orthologues Suggests a Functional Role. PLoS Computational Biology. 8(2). e1002356–e1002356. 5 indexed citations
12.
Miklós, István & Éric Tannier. (2012). Approximating the number of Double Cut-and-Join scenarios. Theoretical Computer Science. 439. 30–40. 6 indexed citations
13.
Novak, Adam M., et al.. (2010). Reticular alignment: A progressive corner-cutting method for multiple sequence alignment. BMC Bioinformatics. 11(1). 570–570. 13 indexed citations
14.
Erdős, Péter L., István Miklós, & Zoltán Toroczkai. (2010). A Simple Havel–Hakimi Type Algorithm to Realize Graphical Degree Sequences of Directed Graphs. The Electronic Journal of Combinatorics. 17(1). 27 indexed citations
15.
Miklós, István & Éric Tannier. (2010). Bayesian sampling of genomic rearrangement scenarios via double cut and join. Bioinformatics. 26(24). 3012–3019. 9 indexed citations
16.
Satija, Rahul, Adam M. Novak, István Miklós, Rune B. Lyngsø, & Jotun Hein. (2009). BigFoot: Bayesian alignment and phylogenetic footprinting with MCMC. BMC Evolutionary Biology. 9(1). 217–217. 22 indexed citations
17.
Miklós, István, Adam M. Novak, Rahul Satija, Rune B. Lyngsø, & Jotun Hein. (2009). Stochastic models of sequence evolution including insertion—deletion events. Statistical Methods in Medical Research. 18(5). 453–485. 13 indexed citations
18.
Miklós, István & Aaron E. Darling. (2009). Efficient Sampling of Parsimonious Inversion Histories with Application to Genome Rearrangement in Yersinia. Genome Biology and Evolution. 1. 153–164. 10 indexed citations
19.
Darling, Aaron E., István Miklós, & Mark A. Ragan. (2008). Dynamics of Genome Rearrangement in Bacterial Populations. PLoS Genetics. 4(7). e1000128–e1000128. 166 indexed citations
20.
Meyer, Irmtraud M. & István Miklós. (2007). SimulFold: Simultaneously Inferring RNA Structures Including Pseudoknots, Alignments, and Trees Using a Bayesian MCMC Framework. PLoS Computational Biology. 3(8). e149–e149. 58 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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