Mohammad Ilyas

8.6k total citations · 2 hit papers
121 papers, 6.1k citations indexed

About

Mohammad Ilyas is a scholar working on Oncology, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Mohammad Ilyas has authored 121 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Oncology, 44 papers in Molecular Biology and 44 papers in Pathology and Forensic Medicine. Recurrent topics in Mohammad Ilyas's work include Genetic factors in colorectal cancer (42 papers), Colorectal Cancer Treatments and Studies (24 papers) and Cancer Genomics and Diagnostics (21 papers). Mohammad Ilyas is often cited by papers focused on Genetic factors in colorectal cancer (42 papers), Colorectal Cancer Treatments and Studies (24 papers) and Cancer Genomics and Diagnostics (21 papers). Mohammad Ilyas collaborates with scholars based in United Kingdom, United States and Egypt. Mohammad Ilyas's co-authors include Ian Tomlinson, Walter F. Bodmer, Andrew Rowan, J. Sträub, Massimo Pignatelli, Marcos Gelos, H. J. Buhr, Mary Pat Moyer, C. Hanski and E O Riecken and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and SHILAP Revista de lepidopterología.

In The Last Decade

Mohammad Ilyas

118 papers receiving 6.0k citations

Hit Papers

Target genes of β-catenin–T cell-factor/lymphoid-enhancer... 1999 2026 2008 2017 1999 2019 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Ilyas United Kingdom 40 3.2k 2.5k 2.0k 1.1k 795 121 6.1k
Aaron Pollett Canada 33 2.6k 0.8× 3.9k 1.5× 1.3k 0.6× 1.7k 1.5× 710 0.9× 87 6.8k
Wolfgang Dietmaier Germany 41 2.5k 0.8× 2.3k 0.9× 1.9k 1.0× 1.4k 1.3× 1.4k 1.7× 135 6.2k
Nicholas J. Hawkins Australia 38 2.2k 0.7× 2.5k 1.0× 2.2k 1.1× 1.3k 1.1× 557 0.7× 102 5.4k
Steven M. Powell United States 32 4.7k 1.5× 2.6k 1.0× 2.4k 1.2× 1.6k 1.4× 1.2k 1.6× 68 8.0k
Andrew M. Hanby United Kingdom 49 3.3k 1.0× 2.6k 1.1× 1.5k 0.8× 2.2k 2.0× 1.2k 1.5× 128 7.5k
Míriam Cuatrecasas Spain 43 2.9k 0.9× 2.3k 0.9× 952 0.5× 1.7k 1.5× 1.0k 1.3× 183 6.3k
Frank T. Kolligs Germany 40 2.9k 0.9× 1.6k 0.6× 866 0.4× 809 0.7× 832 1.0× 106 5.1k
Viviana Bazan Italy 42 2.7k 0.8× 3.1k 1.2× 1.1k 0.6× 2.0k 1.8× 550 0.7× 191 6.3k
Peter T. Simpson Australia 38 2.3k 0.7× 2.0k 0.8× 1.3k 0.6× 2.4k 2.1× 412 0.5× 105 5.1k
Shikha Bose United States 43 6.3k 2.0× 2.6k 1.1× 1.6k 0.8× 2.1k 1.9× 1.1k 1.4× 109 10.2k

Countries citing papers authored by Mohammad Ilyas

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Ilyas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Ilyas

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Ilyas. A scholar is included among the top collaborators of Mohammad Ilyas 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 Mohammad Ilyas. Mohammad Ilyas 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.
2.
Fadhil, Wakkas, Nigel P. Mongan, Arvydas Laurinavičius, et al.. (2023). Activated tissue resident memory T-cells (CD8+CD103+CD39+) uniquely predict survival in left sided “immune-hot” colorectal cancers. Frontiers in Immunology. 14. 1057292–1057292. 12 indexed citations
3.
Elsheikh, Somaia, Teresa P. Raposo, Wakkas Fadhil, et al.. (2020). Ran GTPase is an independent prognostic marker in malignant melanoma which promotes tumour cell migration and invasion. Journal of Clinical Pathology. 75(1). 24–29. 4 indexed citations
4.
Monahan, Kevin, Nicola Bradshaw, Sunil Dolwani, et al.. (2019). Guidelines for the management of hereditary colorectal cancer from the British Society of Gastroenterology (BSG)/Association of Coloproctology of Great Britain and Ireland (ACPGBI)/United Kingdom Cancer Genetics Group (UKCGG). Gut. 69(3). 411–444. 255 indexed citations breakdown →
5.
Asiri, Abdulaziz, et al.. (2018). TGF β1‐induced cell motility but not cell proliferation is mediated through Cten in colorectal cancer. International Journal of Experimental Pathology. 99(6). 323–330. 16 indexed citations
6.
Muhammad, Belal A., Roya Babaei‐Jadidi, Anas Saadeddin, et al.. (2018). FLYWCH1, a Novel Suppressor of Nuclear β-Catenin, Regulates Migration and Morphology in Colorectal Cancer. Molecular Cancer Research. 16(12). 1977–1990. 18 indexed citations
8.
Raposo, Teresa P., et al.. (2018). CD10 inhibits cell motility but expression is associated with advanced stage disease in colorectal cancer. Experimental and Molecular Pathology. 104(3). 190–198. 8 indexed citations
9.
Fadhil, Wakkas, et al.. (2017). QMC-PCRx: a novel method for rapid mutation detection. Journal of Clinical Pathology. 70(8). 702–711. 2 indexed citations
11.
Tewari, Nilanjana, Abed M. Zaitoun, Arvind Arora, et al.. (2013). The presence of tumour-associated lymphocytes confers a good prognosis in pancreatic ductal adenocarcinoma: an immunohistochemical study of tissue microarrays. BMC Cancer. 13(1). 436–436. 65 indexed citations
12.
Fadhil, Wakkas, et al.. (2012). The utility of diagnostic biopsy specimens for predictive molecular testing in colorectal cancer. Histopathology. 61(6). 1117–1124. 20 indexed citations
13.
AlGhamdi, Saleh, Abdulkader M. Albasri, Salih Ibrahem, et al.. (2011). Cten Is Targeted by Kras Signalling to Regulate Cell Motility in the Colon and Pancreas. PLoS ONE. 6(6). e20919–e20919. 34 indexed citations
14.
Aloysius, Mark M., Abed M. Zaitoun, Timothy E. Bates, et al.. (2009). Complete absence of M2-pyruvate kinase expression in benign pancreatic ductal epithelium and pancreaticobiliary and duodenal neoplasia. BMC Cancer. 9(1). 327–327. 10 indexed citations
16.
Martínez, Cristina, et al.. (2005). Expression profiling of murine intestinal adenomas reveals early deregulation of multiple matrix metalloproteinase (Mmp) genes. The Journal of Pathology. 206(1). 100–110. 14 indexed citations
17.
Ellison, David H., Richard Poulsom, Mohammad Ilyas, et al.. (2001). A rapid method for the analysis of cell proliferation and survival in intestinal adenoma from the Apc(Min) mouse. British Journal of Cancer. 85. 39–39. 1 indexed citations
18.
Ilyas, Mohammad, Xingpei Hao, Katalin A. Wilkinson, et al.. (1998). Loss of Bcl-2 expression correlates with tumour recurrence in colorectal cancer. Gut. 43(3). 383–387. 39 indexed citations
19.
Ilyas, Mohammad & I C Talbot. (1995). p53 expression in ulcerative colitis: a longitudinal study.. Gut. 37(6). 802–804. 29 indexed citations
20.
Ilyas, Mohammad, et al.. (1995). The use of the polymerase chain reaction in the diagnosis of B‐cell lymphomas from formalin‐fixed paraffin‐embedded tissue. Histopathology. 26(4). 333–338. 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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