Hamid Pezeshk

1.2k total citations
65 papers, 868 citations indexed

About

Hamid Pezeshk is a scholar working on Molecular Biology, Statistics and Probability and Genetics. According to data from OpenAlex, Hamid Pezeshk has authored 65 papers receiving a total of 868 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 13 papers in Statistics and Probability and 11 papers in Genetics. Recurrent topics in Hamid Pezeshk's work include RNA and protein synthesis mechanisms (14 papers), Machine Learning in Bioinformatics (13 papers) and Protein Structure and Dynamics (13 papers). Hamid Pezeshk is often cited by papers focused on RNA and protein synthesis mechanisms (14 papers), Machine Learning in Bioinformatics (13 papers) and Protein Structure and Dynamics (13 papers). Hamid Pezeshk collaborates with scholars based in Iran, United Kingdom and Germany. Hamid Pezeshk's co-authors include John Gittins, Mehdi Sadeghi, Changiz Eslahchi, Sayed‐Amir Marashi, Gholamreza Nabi Bidhendi, Ali Torabian, Mehran Habibi-Rezaei, Naser Mehrdadi, Masoud Latifi and Farhang Akbar‐Khanzadeh and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Hamid Pezeshk

64 papers receiving 840 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hamid Pezeshk Iran 16 306 192 158 93 80 65 868
Peter Carl Germany 13 155 0.5× 13 0.1× 71 0.4× 4 0.0× 87 1.1× 19 662
Liming China 14 90 0.3× 3 0.0× 32 0.2× 241 2.6× 53 0.7× 139 969
Joep Vanlier Netherlands 12 342 1.1× 18 0.1× 3 0.0× 42 0.5× 146 1.8× 16 759
Yuting Wei China 15 50 0.2× 59 0.3× 7 0.0× 14 0.2× 50 0.6× 69 646
Alejandro Heredia‐Langner United States 13 159 0.5× 15 0.1× 2 0.0× 96 1.0× 98 1.2× 37 669
Xinyuan Zhang China 15 93 0.3× 7 0.0× 8 0.1× 11 0.1× 45 0.6× 65 859
Yalin Chen China 16 174 0.6× 44 0.2× 3 0.0× 5 0.1× 27 0.3× 48 654
Jinchun Zhang China 17 325 1.1× 4 0.0× 12 0.1× 17 0.2× 64 0.8× 83 880
Shulin Zhang China 14 27 0.1× 8 0.0× 24 0.2× 4 0.0× 29 0.4× 50 625
Yongku Kim South Korea 13 16 0.1× 75 0.4× 24 0.2× 50 0.5× 40 0.5× 94 914

Countries citing papers authored by Hamid Pezeshk

Since Specialization
Citations

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

Fields of papers citing papers by Hamid Pezeshk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hamid Pezeshk

This figure shows the co-authorship network connecting the top 25 collaborators of Hamid Pezeshk. A scholar is included among the top collaborators of Hamid Pezeshk 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 Hamid Pezeshk. Hamid Pezeshk 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.
Badv, Reza Shervin, et al.. (2022). Sexual Dimorphism in Telomere Length in Childhood Autism. Journal of Autism and Developmental Disorders. 53(5). 2050–2061. 6 indexed citations
2.
Arefian, Ehsan, et al.. (2020). A meta-analysis of gene expression data highlights synaptic dysfunction in the hippocampus of brains with Alzheimer’s disease. Scientific Reports. 10(1). 8384–8384. 20 indexed citations
3.
Pezeshk, Hamid, et al.. (2020). Inter-protein residue covariation information unravels physically interacting protein dimers. BMC Bioinformatics. 21(1). 584–584. 4 indexed citations
4.
Sharifi‐Zarchi, Ali, Daniela Gerovska, Kenjiro Adachi, et al.. (2017). DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism. BMC Genomics. 18(1). 964–964. 73 indexed citations
5.
Nikolaev, Andrey R., et al.. (2017). Task modulates functional connectivity networks in free viewing behavior. NeuroImage. 159. 289–301. 13 indexed citations
6.
Pezeshk, Hamid, et al.. (2016). MGP-HMM: Detecting genome-wide CNVs using an HMM for modeling mate pair insertion sizes and read counts. Mathematical Biosciences. 279. 53–62. 2 indexed citations
7.
Mahini, Hamid, et al.. (2014). Natural Biased Coin Encoded in the Genome Determines Cell Strategy. PLoS ONE. 9(8). e103569–e103569. 2 indexed citations
8.
Pezeshk, Hamid, et al.. (2013). A clustering approach for estimating parameters of a profile hidden Markov model. International Journal of Data Mining and Bioinformatics. 8(1). 66–66. 2 indexed citations
9.
Safikhani, Zhaleh, Mehdi Sadeghi, Hamid Pezeshk, & Changiz Eslahchi. (2013). SSP: An interval integer linear programming for de novo transcriptome assembly and isoform discovery of RNA-seq reads. Genomics. 102(5-6). 507–514. 8 indexed citations
10.
Pezeshk, Hamid, et al.. (2013). Generalized Baum-Welch Algorithm Based on the Similarity between Sequences. PLoS ONE. 8(12). e80565–e80565. 6 indexed citations
11.
Pezeshk, Hamid, et al.. (2012). THE EFFECTS OF TEMPERATURE AND BIRTH WEIGHT ON THE TRANSITION RATE OF HYPOTHERMIA IN HOSPITALIZED NEONATES USING MARKOV MODELS. Tehran University Medical Journal TUMS Publications. 70(5). 282–288. 4 indexed citations
12.
Ghazizade, Mahdi Jalili, et al.. (2009). Evaluating the Recovery Potential of Solid Wastes. International Journal of Environmental Research. 3(4). 681–690. 4 indexed citations
13.
Sadeghi, Mehdi, et al.. (2009). Global haplotype partitioning for maximal associated SNP pairs. BMC Bioinformatics. 10(1). 269–269. 6 indexed citations
14.
Pezeshk, Hamid, et al.. (2009). A Segmental Semi Markov Model for protein secondary structure prediction. Mathematical Biosciences. 221(2). 130–135. 7 indexed citations
15.
Mirzaie, Mehdi, Changiz Eslahchi, Hamid Pezeshk, & Mehdi Sadeghi. (2009). A distance‐dependent atomic knowledge‐based potential and force for discrimination of native structures from decoys. Proteins Structure Function and Bioinformatics. 77(2). 454–463. 15 indexed citations
16.
Pezeshk, Hamid, et al.. (2008). The choice of sample size: a mixed Bayesian / frequentist approach. Statistical Methods in Medical Research. 18(2). 183–194. 6 indexed citations
17.
Sadeghi, Mehdi, et al.. (2008). Impact of residue accessible surface area on the prediction of protein secondary structures. BMC Bioinformatics. 9(1). 357–357. 33 indexed citations
18.
Sadeghi, Mehdi, et al.. (2008). PROSIGN: A method for protein secondary structure assignment based on three-dimensional coordinates of consecutive Cα atoms. Computational Biology and Chemistry. 32(6). 406–411. 18 indexed citations
19.
Pezeshk, Hamid, et al.. (2008). Protein secondary structure prediction using three neural networks and a segmental semi Markov model. Mathematical Biosciences. 217(2). 145–150. 25 indexed citations
20.
Marashi, Sayed‐Amir, Hani Goodarzi, Mehdi Sadeghi, Changiz Eslahchi, & Hamid Pezeshk. (2005). Importance of RNA secondary structure information for yeast donor and acceptor splice site predictions by neural networks. Computational Biology and Chemistry. 30(1). 50–57. 13 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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