Ladan Teimoori‐Toolabi

1.6k total citations
75 papers, 1.2k citations indexed

About

Ladan Teimoori‐Toolabi is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Ladan Teimoori‐Toolabi has authored 75 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Molecular Biology, 20 papers in Cancer Research and 17 papers in Oncology. Recurrent topics in Ladan Teimoori‐Toolabi's work include Epigenetics and DNA Methylation (16 papers), MicroRNA in disease regulation (14 papers) and Cancer-related gene regulation (12 papers). Ladan Teimoori‐Toolabi is often cited by papers focused on Epigenetics and DNA Methylation (16 papers), MicroRNA in disease regulation (14 papers) and Cancer-related gene regulation (12 papers). Ladan Teimoori‐Toolabi collaborates with scholars based in Iran, Sweden and United States. Ladan Teimoori‐Toolabi's co-authors include Kayhan Azadmanesh, Fatemeh Zare, Elham Fakhr, Sirous Zeinali, Pezhman Fard‐Esfahani, Ali Afgar, Farzad Rajaei, Masoumeh Azizi, Mona Salimi and Amirhosein Mehrtash and has published in prestigious journals such as PLoS ONE, Cancer Research and Scientific Reports.

In The Last Decade

Ladan Teimoori‐Toolabi

72 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ladan Teimoori‐Toolabi Iran 19 786 409 248 127 96 75 1.2k
Boan Li China 22 972 1.2× 333 0.8× 256 1.0× 115 0.9× 116 1.2× 65 1.4k
Lei Hu China 20 779 1.0× 483 1.2× 198 0.8× 55 0.4× 76 0.8× 38 1.2k
Qianqian Yin China 20 1.0k 1.3× 209 0.5× 201 0.8× 100 0.8× 71 0.7× 63 1.4k
Alireza Isazadeh Iran 21 490 0.6× 234 0.6× 184 0.7× 118 0.9× 56 0.6× 53 961
Nan Jia China 19 831 1.1× 247 0.6× 188 0.8× 150 1.2× 62 0.6× 52 1.2k
Yonghua Bao China 20 707 0.9× 384 0.9× 168 0.7× 91 0.7× 76 0.8× 41 1.2k
Hyo-Jong Kim South Korea 11 783 1.0× 186 0.5× 191 0.8× 143 1.1× 120 1.3× 11 1.1k
Lina He United States 18 872 1.1× 315 0.8× 180 0.7× 94 0.7× 234 2.4× 32 1.4k
Richard Beniston United Kingdom 13 957 1.2× 143 0.3× 537 2.2× 68 0.5× 97 1.0× 14 1.3k
Xue Zhang China 19 1.2k 1.5× 506 1.2× 298 1.2× 52 0.4× 90 0.9× 71 1.6k

Countries citing papers authored by Ladan Teimoori‐Toolabi

Since Specialization
Citations

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

Fields of papers citing papers by Ladan Teimoori‐Toolabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ladan Teimoori‐Toolabi. 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 Ladan Teimoori‐Toolabi. The network helps show where Ladan Teimoori‐Toolabi may publish in the future.

Co-authorship network of co-authors of Ladan Teimoori‐Toolabi

This figure shows the co-authorship network connecting the top 25 collaborators of Ladan Teimoori‐Toolabi. A scholar is included among the top collaborators of Ladan Teimoori‐Toolabi 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 Ladan Teimoori‐Toolabi. Ladan Teimoori‐Toolabi 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.
Teimoori‐Toolabi, Ladan, et al.. (2025). Targeted cancer treatment using a novel EGFR-specific Fc-fusion peptide based on GE11 peptide. Scientific Reports. 15(1). 5107–5107. 3 indexed citations
2.
Najafipour, Reza, et al.. (2025). MiR-3664-3p through suppressing ABCG2, CYP3A4, MCL1, and MLH1 increases the sensitivity of colorectal cancer cells to irinotecan. Heliyon. 11(3). e41933–e41933. 3 indexed citations
3.
Teimoori‐Toolabi, Ladan, Ramin Sarrami‐Forooshani, Mahdieh Shokrollahi Barough, et al.. (2023). Looking for biomarkers in interferon response pathway to predict response to oncolytic HSV-1 in breast cancer: An ex vivo study. Cancer Biomarkers. 38(1). 37–47. 2 indexed citations
4.
Afgar, Ali, et al.. (2023). MiR-548c-3p through suppressing Tyms and Abcg2 increases the sensitivity of colorectal cancer cells to 5-fluorouracil. Heliyon. 9(11). e21775–e21775. 3 indexed citations
5.
Poorebrahim, Mansour, Mohammad Foad Abazari, Behzad Shahbazi, et al.. (2022). Multi-targeting of K-Ras domains and mutations by peptide and small molecule inhibitors. PLoS Computational Biology. 18(4). e1009962–e1009962. 5 indexed citations
6.
Shahbazi, Behzad, et al.. (2022). Computational assessment of pigment epithelium-derived factor as an anti-cancer protein during its interaction with the receptors. Journal of Biomolecular Structure and Dynamics. 41(10). 4575–4591. 6 indexed citations
7.
Azizi, Fereidoun, et al.. (2022). The Epigenetic Modification of SLC5A8 in Papillary Thyroid Carcinoma and its Effects on Clinic-Pathological Features. Iranian Journal of Public Health. 51(3). 634–642. 3 indexed citations
8.
Shahbazi, Behzad, Ladan Mafakher, & Ladan Teimoori‐Toolabi. (2022). Different compounds against Angiotensin-Converting Enzyme 2 (ACE2) receptor potentially containing the infectivity of SARS-CoV-2: an in silico study. Journal of Molecular Modeling. 28(4). 82–82. 12 indexed citations
9.
10.
Poorebrahim, Mansour, et al.. (2019). Identification of candidate genes and miRNAs for sensitizing resistant colorectal cancer cells to oxaliplatin and irinotecan. Cancer Chemotherapy and Pharmacology. 85(1). 153–171. 11 indexed citations
11.
Mosaffa, Fatemeh, et al.. (2018). Altered DNA methyltransferases promoter methylation and mRNA expression are associated with tamoxifen response in breast tumors. Journal of Cellular Physiology. 233(9). 7305–7319. 32 indexed citations
12.
Teimoori‐Toolabi, Ladan, et al.. (2018). Among autophagy genes, ATG16L1 but not IRGM is associated with Crohn's disease in Iranians. Gene. 675. 176–184. 6 indexed citations
13.
Sedaghat, Fatemeh, Makan Cheraghpour, Seyed Ahmad Hosseini, et al.. (2018). Hypomethylation of NANOG promoter in colonic mucosal cells of obese patients: a possible role of NF-κB. British Journal Of Nutrition. 122(5). 499–508. 10 indexed citations
14.
15.
Teimoori‐Toolabi, Ladan, et al.. (2017). Evaluation of an Albumin-Binding Domain Protein Fused to Recombinant Human IL-2 and Its Effects on the Bioactivity and Serum Half-Life of the Cytokine. Iranian Biomedical Journal. 21(2). 77–83. 14 indexed citations
16.
Hashemzadeh, Shahriar, et al.. (2016). Detection of aberrant methylated SEPT9 and NTRK3 genes in sporadic colorectal cancer patients as a potential diagnostic biomarker. Oncology Letters. 12(6). 5335–5343. 23 indexed citations
17.
Rajaei, Farzad, et al.. (2016). Molecular alterations contributing to pancreatic cancer chemoresistance. Pancreatology. 17(2). 310–320. 36 indexed citations
18.
Bakhshandeh, Behnaz, et al.. (2014). TCF4 silencing sensitizes the colon cancer cell line to oxaliplatin as a common chemotherapeutic drug. Anti-Cancer Drugs. 25(8). 908–916. 17 indexed citations
19.
Teimoori‐Toolabi, Ladan, Kayhan Azadmanesh, & Sirous Zeinali. (2010). Selective Suicide Gene Therapy of Colon Cancer Cell Lines Exploiting Fibroblast Growth Factor 18 Promoter. Cancer Biotherapy and Radiopharmaceuticals. 25(1). 105–116. 17 indexed citations
20.
Seifati, Seyed Morteza, et al.. (2004). Apolipoprotein E Genotype and Age at Menopause. Annals of the New York Academy of Sciences. 1019(1). 564–567. 17 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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