Amir Feizi

1.9k total citations
22 papers, 1.2k citations indexed

About

Amir Feizi is a scholar working on Molecular Biology, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Amir Feizi has authored 22 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 5 papers in Biomedical Engineering and 4 papers in Artificial Intelligence. Recurrent topics in Amir Feizi's work include Microbial Metabolic Engineering and Bioproduction (5 papers), Biofuel production and bioconversion (5 papers) and Fungal and yeast genetics research (5 papers). Amir Feizi is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (5 papers), Biofuel production and bioconversion (5 papers) and Fungal and yeast genetics research (5 papers). Amir Feizi collaborates with scholars based in Sweden, Denmark and Iran. Amir Feizi's co-authors include Jens Nielsen, Dina Petranović, Björn M. Hallström, Steen Buskov, Luis Caspeta, Payam Ghiaci, Yun Chen, Pernilla Wittung‐Stafshede, Juan Carlos Fierro-González and Stéphanie Blockhuys and has published in prestigious journals such as Science, Nature Communications and PLoS ONE.

In The Last Decade

Amir Feizi

21 papers receiving 1.2k citations

Peers

Amir Feizi

PHYSI

EPIDE

Tongcun Zhang China

Nicoletta Guaragnella Italy

Seddik Hammad Egypt

Olga Protchenko United States

Paul A. Rudnick United States

João Azevedo‐Silva Portugal

Ling Fu China

Yao Pan China

Anna Wojakowska Poland

Xiaohui Yang China

Tongcun Zhang China

Amir Feizi

1.2k ×1.5

177 ×0.7

73 ×0.4

PHYSI

86 ×0.7

EPIDE

228 ×2.2

Citations per year, relative to Amir Feizi Amir Feizi (= 1×) peers Tongcun Zhang

Countries citing papers authored by Amir Feizi

Since Specialization

Citations

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

Fields of papers citing papers by Amir Feizi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amir Feizi

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

All Works

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20 of 20 papers shown

Movassagh, Hesam, Mary Prunicki, Abhinav Kaushik, et al.. (2023). Proinflammatory polarization of monocytes by particulate air pollutants is mediated by induction of trained immunity in pediatric asthma. Allergy. 78(7). 1922–1933. 11 indexed citations

Feizi, Amir & Alireza Nazemi. (2022). Classifying random variables based on support vector machine and a neural network scheme. Journal of Experimental & Theoretical Artificial Intelligence. 36(5). 679–702. 3 indexed citations

Li, Feiran, Yu Chen, Yanyan Wang, et al.. (2022). Improving recombinant protein production by yeast through genome-scale modeling using proteome constraints. Nature Communications. 13(1). 2969–2969. 41 indexed citations

Feizi, Amir, et al.. (2021). Solving the stochastic support vector regression with probabilistic constraints by a high-performance neural network model. Engineering With Computers. 38(S2). 1005–1020. 8 indexed citations

Gutierrez, Jahir M., Amir Feizi, Shangzhong Li, et al.. (2020). Genome-scale reconstructions of the mammalian secretory pathway predict metabolic costs and limitations of protein secretion. Nature Communications. 11(1). 68–68. 81 indexed citations

Jong, Jasper M. A. de, Wenfei Sun, Nuno D. Pires, et al.. (2019). Human brown adipose tissue is phenocopied by classical brown adipose tissue in physiologically humanized mice. Nature Metabolism. 1(8). 830–843. 92 indexed citations

Jespersen, Naja Zenius, Amir Feizi, Eline Sandvig Andersen, et al.. (2019). Heterogeneity in the perirenal region of humans suggests presence of dormant brown adipose tissue that contains brown fat precursor cells. Molecular Metabolism. 24. 30–43. 85 indexed citations

Robinson, Jonathan L., Amir Feizi, Mathias Uhlén, & Jens Nielsen. (2019). A Systematic Investigation of the Malignant Functions and Diagnostic Potential of the Cancer Secretome. Cell Reports. 26(10). 2622–2635.e5. 54 indexed citations

Feizi, Amir, Francesco Gatto, Mathias Uhlén, & Jens Nielsen. (2017). Human protein secretory pathway genes are expressed in a tissue-specific pattern to match processing demands of the secretome. npj Systems Biology and Applications. 3(1). 22–22. 25 indexed citations

10.

Blockhuys, Stéphanie, Emanuele Celauro, Camilla Hildesjö, et al.. (2016). Defining the human copper proteome and analysis of its expression variation in cancers. Metallomics. 9(2). 112–123. 210 indexed citations

11.

Fletcher, Eugene, Amir Feizi, Markus M.M. Bisschops, et al.. (2016). Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments. Metabolic Engineering. 39. 19–28. 81 indexed citations

12.

Bengtsson‐Palme, Johan, Fredrik Boulund, Amir Feizi, et al.. (2016). Strategies to improve usability and preserve accuracy in biological sequence databases. PROTEOMICS. 16(18). 2454–2460. 18 indexed citations

13.

Fletcher, Eugene, Amir Feizi, Sung Soo Kim, Verena Siewers, & Jens Nielsen. (2015). RNA-seq analysis of Pichia anomala reveals important mechanisms required for survival at low pH. Microbial Cell Factories. 14(1). 143–143. 21 indexed citations

14.

Feizi, Amir, Amir Banaei‐Esfahani, & Jens Nielsen. (2015). HCSD: the human cancer secretome database. Database. 2015. bav051–bav051. 25 indexed citations

15.

Liu, Lifang, Amir Feizi, Tobias Österlund, Carsten Hjort, & Jens Nielsen. (2014). Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae. BMC Systems Biology. 8(1). 73–73. 32 indexed citations

16.

Caspeta, Luis, Yun Chen, Payam Ghiaci, et al.. (2014). Altered sterol composition renders yeast thermotolerant. Science. 346(6205). 75–78. 334 indexed citations

17.

Feizi, Amir & Sergio Bordel. (2013). Metabolic and protein interaction sub-networks controlling the proliferation rate of cancer cells and their impact on patient survival. Scientific Reports. 3(1). 3041–3041. 12 indexed citations

18.

Feizi, Amir, Tobias Österlund, Dina Petranović, Sergio Bordel, & Jens Nielsen. (2013). Genome-Scale Modeling of the Protein Secretory Machinery in Yeast. PLoS ONE. 8(5). e63284–e63284. 56 indexed citations

19.

Manshaei, Roozbeh, Mahdi Aliyari Shoorehdeli, Amir Feizi, et al.. (2012). Hybrid-Controlled Neurofuzzy Networks Analysis Resulting in Genetic Regulatory Networks Reconstruction. PubMed. 2012. 1–16. 4 indexed citations

20.

Manshaei, Roozbeh, et al.. (2008). Time series ene expression data clustering and pattern extraction in Arabidopsis thaliana phosphatase-encoding genes. 1. 1–6. 4 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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