James M. Hogan

915 total citations
59 papers, 541 citations indexed

About

James M. Hogan is a scholar working on Molecular Biology, Artificial Intelligence and Information Systems. According to data from OpenAlex, James M. Hogan has authored 59 papers receiving a total of 541 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 13 papers in Artificial Intelligence and 10 papers in Information Systems. Recurrent topics in James M. Hogan's work include Genomics and Phylogenetic Studies (19 papers), Machine Learning in Bioinformatics (13 papers) and Algorithms and Data Compression (8 papers). James M. Hogan is often cited by papers focused on Genomics and Phylogenetic Studies (19 papers), Machine Learning in Bioinformatics (13 papers) and Algorithms and Data Compression (8 papers). James M. Hogan collaborates with scholars based in Australia, United States and India. James M. Hogan's co-authors include Helen Bergen, Richard Thomas, Michael Towsey, Peter Timms, Sarah Mathews, Stefan Maetschke, Mark A. Ragan, Yao-ban Chan, Cheong Xin Chan and Guillaume Bernard and has published in prestigious journals such as Bioinformatics, PLoS ONE and Scientific Reports.

In The Last Decade

James M. Hogan

53 papers receiving 506 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
James M. Hogan Australia	12	183	158	90	86	37	59	541
Duncan D. Ruiz Brazil	16	119 0.7×	213 1.3×	102 1.1×	186 2.2×	21 0.6×	64	648
Donald L. Bitzer United States	16	206 1.1×	134 0.8×	35 0.4×	63 0.7×	65 1.8×	78	835
Humberto Carrillo-Calvet Mexico	10	285 1.6×	229 1.4×	26 0.3×	40 0.5×	22 0.6×	40	595
Larry Wall Switzerland	6	139 0.8×	318 2.0×	28 0.3×	215 2.5×	23 0.6×	11	786
Marco Gaertler Germany	7	176 1.0×	276 1.7×	82 0.9×	55 0.6×	13 0.4×	10	879
Solon P. Pissis United Kingdom	13	348 1.9×	350 2.2×	45 0.5×	58 0.7×	8 0.2×	115	700
Cam Macdonell Canada	8	376 2.1×	83 0.5×	22 0.2×	39 0.5×	26 0.7×	13	586
Tobias Kuhn Netherlands	13	104 0.6×	316 2.0×	30 0.3×	209 2.4×	10 0.3×	56	605
Kenneth E. Whelan United Kingdom	4	357 2.0×	248 1.6×	33 0.4×	37 0.4×	14 0.4×	4	884

Countries citing papers authored by James M. Hogan

Since Specialization

Citations

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

Fields of papers citing papers by James M. Hogan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James M. Hogan. 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 James M. Hogan. The network helps show where James M. Hogan may publish in the future.

Co-authorship network of co-authors of James M. Hogan

This figure shows the co-authorship network connecting the top 25 collaborators of James M. Hogan. A scholar is included among the top collaborators of James M. Hogan 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 James M. Hogan. James M. Hogan 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

Geva, Shlomo, et al.. (2022). Metagenomic Geolocation Using Read Signatures. Frontiers in Genetics. 13. 643592–643592. 2 indexed citations

Hogan, James M., et al.. (2021). Sequence Representations and Their Utility for Predicting Protein-Protein Interactions. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(1). 646–657. 4 indexed citations

Hogan, James M., et al.. (2020). Learning supervised embeddings for large scale sequence comparisons. PLoS ONE. 15(3). e0216636–e0216636. 4 indexed citations

Petit, Robert A., James M. Hogan, Matthew Ezewudo, Sandeep J. Joseph, & Timothy D. Read. (2018). Fine-scale differentiation between Bacillus anthracis and Bacillus cereus group signatures in metagenome shotgun data. PeerJ. 6. e5515–e5515. 4 indexed citations

Geva, Shlomo, James M. Hogan, Flavia Huygens, et al.. (2018). Rapid analysis of metagenomic data using signature-based clustering. BMC Bioinformatics. 19(S20). 509–509. 2 indexed citations

Heinrich, Julian, Aiping Wu, Markus Rittenbruch, et al.. (2016). Evaluating Viewpoint Entropy for Ribbon Representation of Protein Structure. Computer Graphics Forum. 35(3). 181–190. 1 indexed citations

O’Donoghue, Séan, et al.. (2016). Using videogames to improve molecular graphics tools. 646–648. 1 indexed citations

Hogan, James M., et al.. (2014). Weighted tree kernels for sequence analysis.. The European Symposium on Artificial Neural Networks.

Hogan, James M., et al.. (2014). Locality-sensitive hashing for protein classification. QUT ePrints (Queensland University of Technology). 141–147. 3 indexed citations

10.

Chan, Cheong Xin, Guillaume Bernard, Olivier Poirion, James M. Hogan, & Mark A. Ragan. (2014). Inferring phylogenies of evolving sequences without multiple sequence alignment. Scientific Reports. 4(1). 6504–6504. 1 indexed citations

11.

Hogan, James M., Peter W. H. Holland, Alexander Holloway, Robert A. Petit, & Timothy D. Read. (2013). Read classification for next generation sequencing. QUT ePrints (Queensland University of Technology). 2 indexed citations

12.

Lister, Raymond, Daryl D’Souza, Margaret Hamilton, et al.. (2012). Toward a shared understanding of competency in programming: An invitation to the BABELnot project. QUT ePrints (Queensland University of Technology). 12 indexed citations

13.

Deprèle, Sylvine, B. A. Kashemirov, James M. Hogan, et al.. (2008). Farnesyl pyrophosphate synthase enantiospecificity with a chiral risedronate analog, [6,7-dihydro-5H-cyclopenta[c]pyridin-7-yl(hydroxy)methylene]bis(phosphonic acid) (NE-10501): Synthetic, structural, and modeling studies. Bioorganic & Medicinal Chemistry Letters. 18(9). 2878–2882. 9 indexed citations

14.

Maetschke, Stefan, Michael Towsey, & James M. Hogan. (2007). BioPatML - an XML description language for patterns in biological sequences. QUT ePrints (Queensland University of Technology). 1 indexed citations

15.

Maetschke, Stefan, Michael Towsey, & James M. Hogan. (2006). Bacterial promoter modelling and prediction for E. coli and B. subtilis with Beagle. QUT ePrints (Queensland University of Technology).

16.

Towsey, Michael, J Gordon, & James M. Hogan. (2006). The Prediction of Bacterial Transcription Start Sites using Support Vector Machines. International Journal of Neural Systems. 3 indexed citations

17.

Hogan, James M. & Richard Thomas. (2005). Developing the software engineering team. Queensland's institutional digital repository (The University of Queensland). 42. 203–210. 31 indexed citations

18.

Hogan, James M., et al.. (2005). Tight spirals and industry clients: the modern SE education experience. Queensland's institutional digital repository (The University of Queensland). 42. 217–222. 12 indexed citations

19.

Hogan, James M. & Joachim Diederich. (2001). RECRUITMENT LEARNING OF BOOLEAN FUNCTIONS IN SPARSE RANDOM NETWORKS. International Journal of Neural Systems. 11(6). 537–559. 2 indexed citations

20.

Hogan, James M. & Peter James. (1997). Australian Approaches to Internet Content Regulation.. Australian Computer Journal. 29. 16–23. 1 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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