Monther Alhamdoosh

2.6k total citations
18 papers, 563 citations indexed

About

Monther Alhamdoosh is a scholar working on Molecular Biology, Immunology and Surgery. According to data from OpenAlex, Monther Alhamdoosh has authored 18 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Immunology and 3 papers in Surgery. Recurrent topics in Monther Alhamdoosh's work include Machine Learning and ELM (3 papers), Machine Learning in Bioinformatics (2 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers). Monther Alhamdoosh is often cited by papers focused on Machine Learning and ELM (3 papers), Machine Learning in Bioinformatics (2 papers) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (2 papers). Monther Alhamdoosh collaborates with scholars based in Australia, Switzerland and United Kingdom. Monther Alhamdoosh's co-authors include Dianhui Wang, Milica Ng, Nicholas J. Wilson, Matthew E. Ritchie, Michael J. Wilson, Huy Huynh, Julie M. Sheridan, D. Gabriëls, Muhammed Khlosi and Ahmed Douaik and has published in prestigious journals such as Circulation, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Monther Alhamdoosh

17 papers receiving 557 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Monther Alhamdoosh Australia 11 179 158 61 54 54 18 563
Xintong Yan China 17 250 1.4× 85 0.5× 125 2.0× 20 0.4× 25 0.5× 62 997
Huazhen Wang China 11 160 0.9× 100 0.6× 75 1.2× 32 0.6× 31 0.6× 31 521
Wenjia Xu China 16 158 0.9× 117 0.7× 194 3.2× 27 0.5× 36 0.7× 47 740
Yiwen Lu China 15 83 0.5× 86 0.5× 65 1.1× 12 0.2× 174 3.2× 35 659
Jingyang Gao China 11 163 0.9× 136 0.9× 107 1.8× 15 0.3× 13 0.2× 55 682
Dan Niu China 14 60 0.3× 68 0.4× 55 0.9× 55 1.0× 44 0.8× 108 664
Gang Xue China 11 46 0.3× 222 1.4× 18 0.3× 37 0.7× 89 1.6× 64 777
Kun Shao China 16 64 0.4× 91 0.6× 36 0.6× 243 4.5× 70 1.3× 52 812
Shanzhi Gu China 9 153 0.9× 131 0.8× 323 5.3× 21 0.4× 41 0.8× 17 746

Countries citing papers authored by Monther Alhamdoosh

Since Specialization
Citations

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

Fields of papers citing papers by Monther Alhamdoosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Monther Alhamdoosh

This figure shows the co-authorship network connecting the top 25 collaborators of Monther Alhamdoosh. A scholar is included among the top collaborators of Monther Alhamdoosh 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 Monther Alhamdoosh. Monther Alhamdoosh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Berhan, Asres, Trudi Harris, Jade Jaffar, et al.. (2025). Matrix Softness Induces an Afibrogenic Lipofibroblast Phenotype in Fibroblasts from Patients with Idiopathic Pulmonary Fibrosis. American Journal of Respiratory Cell and Molecular Biology. 73(5). 686–699.
2.
Montellese, Christian, Matthew E. Ritchie, Monther Alhamdoosh, et al.. (2024). An optimized protocol for quality control of gene therapy vectors using nanopore direct RNA sequencing. Genome Research. 34(11). 1966–1975. 2 indexed citations
3.
Martin, Katherine, Cristina Gamell, Tsin Yee Tai, et al.. (2024). Whole blood transcriptomics reveals granulocyte colony‐stimulating factor as a mediator of cardiopulmonary bypass‐induced systemic inflammatory response syndrome. Clinical & Translational Immunology. 13(2). e1490–e1490. 2 indexed citations
4.
You, Yue, Xueyi Dong, Mhairi J. Maxwell, et al.. (2023). Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data. Genome biology. 24(1). 107–107. 6 indexed citations
5.
Gamell, Cristina, Aleksandra Bankovacki, Karen Scalzo‐Inguanti, et al.. (2023). CSL324, a granulocyte colony-stimulating factor receptor antagonist, blocks neutrophil migration markers that are upregulated in hidradenitis suppurativa. British Journal of Dermatology. 188(5). 636–648. 11 indexed citations
6.
Jaffar, Jade, Gregory A. Fishbein, Monther Alhamdoosh, et al.. (2022). Matrix metalloproteinase-7 is increased in lung bases but not apices in idiopathic pulmonary fibrosis. ERJ Open Research. 8(4). 191–2022. 16 indexed citations
7.
Didichenko, Svetlana A., Jacqueline Adam, Monther Alhamdoosh, et al.. (2021). Abstract 10491: CSL112 Suppresses Inflammation in Human Monocyte-Derived Macrophages. Circulation. 144(Suppl_1). 2 indexed citations
8.
Berhan, Asres, Trudi Harris, Jade Jaffar, et al.. (2020). Cellular Microenvironment Stiffness Regulates Eicosanoid Production and Signaling Pathways. American Journal of Respiratory Cell and Molecular Biology. 63(6). 819–830. 26 indexed citations
9.
McRae, Jennifer L., Ingela B. Vikstrom, Anjan K. Bongoni, et al.. (2020). Blockade of the G-CSF Receptor Is Protective in a Mouse Model of Renal Ischemia–Reperfusion Injury. The Journal of Immunology. 205(5). 1433–1440. 10 indexed citations
10.
Figgett, William A., Milica Ng, Monther Alhamdoosh, et al.. (2019). Machine learning applied to whole‐blood RNA‐sequencing data uncovers distinct subsets of patients with systemic lupus erythematosus. Clinical & Translational Immunology. 8(12). e01093–e01093. 32 indexed citations
11.
Koernig, Sandra, Ian K. Campbell, Charley Mackenzie-Kludas, et al.. (2019). Topical application of human-derived Ig isotypes for the control of acute respiratory infection evaluated in a human CD89-expressing mouse model. Mucosal Immunology. 12(4). 1013–1024. 10 indexed citations
12.
Law, Charity W., Monther Alhamdoosh, Shian Su, Gordon K. Smyth, & Matthew E. Ritchie. (2016). RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR [version 1; referees: 3 approved]. SHILAP Revista de lepidopterología. 8 indexed citations
13.
Alhamdoosh, Monther, Milica Ng, Nicholas J. Wilson, et al.. (2016). Combining multiple tools outperforms individual methods in gene set enrichment analyses. Bioinformatics. 33(3). 414–424. 120 indexed citations
14.
Khlosi, Muhammed, Monther Alhamdoosh, Ahmed Douaik, D. Gabriëls, & Wim Cornelis. (2016). Enhanced pedotransfer functions with support vector machines to predict water retention of calcareous soil. European Journal of Soil Science. 67(3). 276–284. 54 indexed citations
15.
Alhamdoosh, Monther & Dianhui Wang. (2014). Fast decorrelated neural network ensembles with random weights. Information Sciences. 264. 104–117. 154 indexed citations
16.
Wang, Dianhui & Monther Alhamdoosh. (2012). Evolutionary extreme learning machine ensembles with size control. Neurocomputing. 102. 98–110. 79 indexed citations
17.
Alhamdoosh, Monther, Castrense Savojardo, Piero Fariselli, & Rita Casadio. (2011). DISULFIDE CONNECTIVITY PREDICTION WITH EXTREME LEARNING MACHINES. 5–14. 1 indexed citations
18.
Savojardo, Castrense, Piero Fariselli, Monther Alhamdoosh, et al.. (2011). Improving the prediction of disulfide bonds in Eukaryotes with machine learning methods and protein subcellular localization. Bioinformatics. 27(16). 2224–2230. 30 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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