Mohammad Pakzad

812 citations
25 papers · 638 · h-index 16

Impact in

  • Genetics top 10%
    • Mesenchymal stem cell research
    • Pluripotent Stem Cells Research
    • CRISPR and Genetic Engineering
    • Extracellular vesicles in disease
    • Renal and related cancers

Papers in

    • Pluripotent Stem Cells Research 15
    • CRISPR and Genetic Engineering 7
    • Renal and related cancers 4
    • Extracellular vesicles in disease 4
    • Tissue Engineering and Regenerative Medicine 6

Mohammad Pakzad

25 papers receiving 630 citations

Peers

Mohammad Pakzad
Comparison fields: 5 of 73
  • Genetics 105
  • Molecular Biology 475
  • Rehabilitation 44
  • Developmental Neuroscience 19
  • Cancer Research 57
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Hitomi Takada Japan
Dejin Zheng China
Teresa Nieto-Miguel Spain
Sylwia Bobis‐Wozowicz Poland
Sonali Rawat India
Kyoung‐Won Ko South Korea
Quanhai Li China
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Jun Yong Kim South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Mohammad Pakzad

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Pakzad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200982
2 200980
3 201965
4 201354
5 200954
6 202041
7 202224
8 202324
9 201421
10 202319
11 201218
12 201417
13
Cloning, expression and functional characterization of in-house prepared human basic fibroblast growth factor.
201317
14 201717
15 202215
16 201715
17 201314
18 201311
19 201310
20 20219

About Mohammad Pakzad

Mohammad Pakzad is a scholar working on Molecular Biology, Surgery, Genetics, Biomedical Engineering and Cancer Research, having authored 25 papers that have together received 638 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (15 papers), CRISPR and Genetic Engineering (7 papers), Tissue Engineering and Regenerative Medicine (6 papers), Mesenchymal stem cell research (5 papers), 3D Printing in Biomedical Research (5 papers), Renal and related cancers (4 papers), Extracellular vesicles in disease (4 papers) and MicroRNA in disease regulation (3 papers). The work is most often cited by research in Genetics (105 citations), Molecular Biology (475 citations), Rehabilitation (44 citations), Developmental Neuroscience (19 citations) and Cancer Research (57 citations). Mohammad Pakzad has collaborated with scholars based in Iran, Germany and Australia. Frequent co-authors include Hossein Baharvand, Seyedeh‐Nafiseh Hassani, Mehdi Totonchi, Ali Seifinejad, Adeleh Taei, Ghasem Hosseini Salekdeh, Sepideh Mollamohammadi, Hamid Gourabi, Abdoreza Nazari and Faezeh Shekari. Their work appears in journals such as Human Reproduction, Life Sciences, Histochemistry and Cell Biology, Molecular BioSystems and Stem Cell Research & Therapy.

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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