Bill Andreopoulos
- Ecology top 10%
- Microbial Community Ecology and Physiology 2
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- Bioinformatics and Genomic Networks 7
- Gene expression and cancer classification 4
- Genomics and Phylogenetic Studies 3
- Microbial Metabolic Engineering and Bioproduction 3
- Protein Structure and Dynamics 2
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- Advanced Clustering Algorithms Research 4
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- Software Engineering Research 2
- Co-authors
- Michael SchroederLöıc A. RoyerXiaogang WangAijun AnNatalie SolonenkoCristina Howard‐VaronaDoina CiobanuJan‐Fang Cheng
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Bill Andreopoulos
19 papers receiving 587 citations
Peers
Comparison fields: 5 of 89
- Ecology 200
- Molecular Biology 348
- Endocrinology 20
- Plant Science 122
- Pollution 36
Countries citing papers authored by Bill Andreopoulos
This map shows the geographic impact of Bill Andreopoulos'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 Bill Andreopoulos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bill Andreopoulos more than expected).
Fields of papers citing papers by Bill Andreopoulos
This network shows the impact of papers produced by Bill Andreopoulos. 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 Bill Andreopoulos. The network helps show where Bill Andreopoulos may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bill Andreopoulos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 142 | |
| 2 | 2019 | 43 | |
| 3 | 2019 | 14 | |
| 4 | 2018 | 81 | |
| 5 | 2016 | 1 | |
| 6 | 2016 | 74 | |
| 7 | 2012 | 20 | |
| 8 | 2011 | 9 | |
| 9 | 2009 | 5 | |
| 10 | 2009 | 26 | |
| 11 | 2008 | 13 | |
| 12 | 2008 | 5 | |
| 13 | 2008 | 85 | |
| 14 | 2007 | 21 | |
| 15 | 2006 | 5 | |
| 16 | 2006 | 16 | |
| 17 | 2006 | 24 | |
| 18 | 2005 | 5 | |
| 19 | 2004 | 7 | |
| 20 | Gene Expression Specification | 2003 | 0 |
About Bill Andreopoulos
Bill Andreopoulos is a scholar working on Artificial Intelligence, Molecular Biology, Plant Science, Information Systems and Cell Biology, having authored 20 papers that have together received 596 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (7 papers), Advanced Clustering Algorithms Research (4 papers), Gene expression and cancer classification (4 papers), Genomics and Phylogenetic Studies (3 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Microbial Community Ecology and Physiology (2 papers), Protein Structure and Dynamics (2 papers) and Software Engineering Research (2 papers). The work is most often cited by research in Ecology (200 citations), Molecular Biology (348 citations), Endocrinology (20 citations), Plant Science (122 citations) and Pollution (36 citations). Bill Andreopoulos has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Michael Schroeder, Löıc A. Royer, Xiaogang Wang, Aijun An, Natalie Solonenko, Cristina Howard‐Varona, Doina Ciobanu, Jan‐Fang Cheng, Heather M. Brewer and Ho Bin Jang. Their work appears in journals such as BMC Bioinformatics, The ISME Journal, Bioinformatics, Nature Microbiology and PLoS Computational Biology.
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.