Glenn T. Colby
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Education top 10%
- Cancer Research
- Health, Toxicology and Mutagenesis
- Co-authors
- Carolyn MattinglyJames L. BoyerJohn N. ForrestKelly PuzioJ. N. ForrestMichael C. RosensteinAllan Peter DavisLynsey Gibbons
- Topics
- Gene expression and cancer classification (5 papers)Bioinformatics and Genomic Networks (3 papers)Innovative Teaching and Learning Methods (2 papers)
- Partner nations
- United States
In The Last Decade
Glenn T. Colby
10 papers receiving 497 citations
Peers
Comparison fields: 5 of 96
- Molecular Biology 310
- Computational Theory and Mathematics 133
- Education 79
- Cancer Research 43
- Health, Toxicology and Mutagenesis 41
Countries citing papers authored by Glenn T. Colby
This map shows the geographic impact of Glenn T. Colby'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 Glenn T. Colby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glenn T. Colby more than expected).
Fields of papers citing papers by Glenn T. Colby
This network shows the impact of papers produced by Glenn T. Colby. 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 Glenn T. Colby. The network helps show where Glenn T. Colby may publish in the future.
Co-authorship network of co-authors of Glenn T. Colby
This figure shows the co-authorship network connecting the top 25 collaborators of Glenn T. Colby. A scholar is included among the top collaborators of Glenn T. Colby 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 Glenn T. Colby. Glenn T. Colby is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 40 | |
| 3 | 12 | |
| 4 | 41 | |
| 5 | The Effects of within Class Grouping on Reading Achievement: A Meta-Analytic Synthesis. | 5 |
| 6 | Supporting Middle-Grades Principals as Instructional Leaders in Mathematics | 1 |
| 7 | Students' Epistemological Beliefs of Mathematics When Taught Using Traditional Versus Reform Curricula in Rural Maine High Schools | 2 |
| 8 | 96 | |
| 9 | 112 | |
| 10 | 29 | |
| 11 | 177 | |
| 12 | 5 |
About Glenn T. Colby
Glenn T. Colby is a scholar working on Developmental and Educational Psychology, Education and Computational Theory and Mathematics, having authored 12 papers that have together received 520 indexed citations. Recurring topics across this work include Gene expression and cancer classification (5 papers), Bioinformatics and Genomic Networks (3 papers) and Innovative Teaching and Learning Methods (2 papers). The work is most often cited by research in Computational Theory and Mathematics (133 citations), Molecular Biology (310 citations) and Pharmacology (30 citations). Glenn T. Colby has collaborated with scholars based in United States. Frequent co-authors include Carolyn Mattingly, James L. Boyer, John N. Forrest, Kelly Puzio, J. N. Forrest, Michael C. Rosenstein, James L. Boyer, Allan Peter Davis, Lynsey Gibbons and Erin Henrick. Their work appears in journals such as Environmental Health Perspectives, Review of Educational Research and Toxicological Sciences.
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.