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James M. Hogan
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2020 – today
- 2023
- [j15]Dhananjay Kimothi
, Pravesh Biyani
, James M. Hogan, Melissa J. Davis
:
Sequence Representations and Their Utility for Predicting Protein-Protein Interactions. IEEE ACM Trans. Comput. Biol. Bioinform. 20(1): 646-657 (2023) - 2022
- [j14]Markus Rittenbruch
, Kellie Vella
, Margot Brereton
, James M. Hogan, Daniel Johnson
, Julian Heinrich, Seán I. O'Donoghue:
Collaborative Sense-Making in Genomic Research: The Role of Visualisation. IEEE Trans. Vis. Comput. Graph. 28(12): 4477-4489 (2022) - 2020
- [j13]Sarah Pilz, Florian Porrmann
, Martin Kaiser
, Jens Hagemeyer, James M. Hogan, Ulrich Rückert:
Accelerating Binary String Comparisons with a Scalable, Streaming-Based System Architecture Based on FPGAs. Algorithms 13(2): 47 (2020)
2010 – 2019
- 2019
- [j12]Guillaume Bernard
, Cheong Xin Chan
, Yao-ban Chan, Xin-Yi Chua
, Yingnan Cong, James M. Hogan, Stefan R. Maetschke
, Mark A. Ragan:
Alignment-free inference of hierarchical and reticulate phylogenomic relationships. Briefings Bioinform. 20(2): 426-435 (2019) - 2018
- [j11]Timothy Chappell, Shlomo Geva, James M. Hogan, Flavia Huygens
, Irani U. Rathnayake, Stephen Rudd, Wayne Kelly, Dimitri Perrin:
Rapid analysis of metagenomic data using signature-based clustering. BMC Bioinform. 19-S(20): 79-93 (2018) - [c28]Timothy Chappell, Shlomo Geva, James M. Hogan, Dimitri Perrin:
Rapid hierarchical clustering of biological sequences. ADCS 2018: 8:1-8:4 - [c27]Lawrence Buckingham, Shlomo Geva, James M. Hogan:
Protein database search using compressed k-mer vocabularies. ADCS 2018: 10:1-10:7 - 2017
- [c26]Timothy Chappell, Shlomo Geva, James M. Hogan:
K-Means Clustering of Biological Sequences. ADCS 2017: 2:1-2:4 - [c25]Timothy Chappell, Shlomo Geva, James M. Hogan, Flavia Huygens
, Wayne Kelly, Dimitri Perrin:
Signature-based clustering for analysis of the wound microbiome. BIBM 2017: 339-346 - [c24]Lawrence Buckingham, Timothy Chappell, James M. Hogan, Shlomo Geva:
Similarity Projection: A Geometric Measure for Comparison of Biological Sequences. eScience 2017: 325-334 - [c23]Samuel Thomas Smith, James Michael Hogan, Xin-Yi Chua
, Margot Brereton
, Daniel M. Johnson
, Markus Rittenbruch
:
Iterative Design and Evaluation of Regulatory Network Visualisation at Scale. eScience 2017: 354-363 - [c22]Dhananjay Kimothi, Ankita Shukla
, Pravesh Biyani, Saket Anand, James M. Hogan:
Metric learning on biological sequence embeddings. SPAWC 2017: 1-5 - 2016
- [j10]Julian Heinrich, Jenny Vuong, Christopher J. Hammang, A. Wu, Markus Rittenbruch
, James M. Hogan, Margot Brereton
, Seán I. O'Donoghue
:
Evaluating Viewpoint Entropy for Ribbon Representation of Protein Structure. Comput. Graph. Forum 35(3): 181-190 (2016) - [c21]Holly Hutson, Daniel M. Johnson, Xin-Yi Chua, James M. Hogan, Margot Brereton, Markus Rittenbruch, Benedetta Frida Baldi, Seán I. O'Donoghue:
Can Videogame Players Inform Better Scientific Visualization'. CHI PLAY (Companion) 2016: 181-187 - [c20]Zachary Fitz-Walter, Seán I. O'Donoghue
, Benedetta Frida Baldi
, James M. Hogan, Daniel M. Johnson
, Margot Brereton
:
Using videogames to improve molecular graphics tools. OZCHI 2016: 646-648 - [i1]Dhananjay Kimothi, Akshay Soni, Pravesh Biyani, James M. Hogan:
Distributed Representations for Biological Sequence Analysis. CoRR abs/1608.05949 (2016) - 2015
- [c19]Xin-Yi Chua
, Lawrence Buckingham, James M. Hogan, Pavel S. Novichkov:
Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff. ICCS 2015: 713-724 - [c18]Samuel A. Brian, Richard N. Thomas
, James M. Hogan, Colin J. Fidge
:
Planting Bugs: A System for Testing Students' Unit Tests. ITiCSE 2015: 45-50 - [c17]Samuel Thomas Smith, James M. Hogan, Markus Rittenbruch
, Daniel M. Johnson
, Margot Brereton
:
Visual Analytics for Large-Scale Bioinformatic Data Sets. OZCHI 2015: 603-607 - 2014
- [c16]Lawrence Buckingham, James M. Hogan, Shlomo Geva, Wayne Kelly:
Locality-Sensitive Hashing for Protein Classification. AusDM 2014: 141-147 - [c15]Lawrence Buckingham, James M. Hogan:
Computational Science for Undergraduate Biologists via QUT.Bio.Excel. ICCS 2014: 1403-1412 - [c14]James M. Hogan, Timothy Peut:
Large Scale Read Classification forNext Generation Sequencing. ICCS 2014: 2003-2012 - 2013
- [c13]Jaspar Cahill, James M. Hogan, Richard N. Thomas
:
Predicting Fault-Prone Software Modules with Rank Sum Classification. Australian Software Engineering Conference 2013: 211-219 - [c12]James M. Hogan, Wayne Kelly, Felicity Newell:
Consensus Sigma-70 Promoter Prediction Using Hadoop. e-Science 2013: 35-44 - 2011
- [b2]Joachim Diederich, Cengiz Günay
, James M. Hogan:
Recruitment Learning. Studies in Computational Intelligence 303, Springer 2011, ISBN 978-3-642-14027-3, pp. 3-281 [contents] - [j9]James M. Hogan, Jiro Sumitomo, Paul Roe, Felicity Newell
:
Biomashups: the new world of exploratory bioinformatics? Concurr. Comput. Pract. Exp. 23(11): 1169-1178 (2011)
2000 – 2009
- 2008
- [j8]Michael W. Towsey
, Peter Timms
, James M. Hogan, Sarah A. Mathews:
The cross-species prediction of bacterial promoters using a support vector machine. Comput. Biol. Chem. 32(5): 359-366 (2008) - [c11]Lawrence Buckingham, James M. Hogan, Paul Roe, Jiro Sumitomo, Michael W. Towsey
:
Comparative Studies Made Simple in GPFlow. CCGRID 2008: 699 - [c10]Jiro Sumitomo, James M. Hogan, Felicity Newell
, Paul Roe:
BioMashups: The New World of Exploratory Bioinformatics? eScience 2008: 422-423 - [c9]Lawrence Buckingham, James M. Hogan, Paul Roe, Jiro Sumitomo, Michael W. Towsey
:
Comparative Studies Simplified in GPFlow. ICCS (3) 2008: 491-500 - 2006
- [j7]James J. Gordon, Michael W. Towsey
, James M. Hogan, Sarah A. Mathews, Peter Timms
:
Improved prediction of bacterial transcription start sites. Bioinform. 22(2): 142-148 (2006) - [j6]Michael W. Towsey
, James J. Gordon, James M. Hogan:
The Prediction of Bacterial Transcription Start Sites Using Svms. Int. J. Neural Syst. 16(5): 363-370 (2006) - 2005
- [c8]James M. Hogan, Richard N. Thomas:
Developing the Software Engineering Team. ACE 2005: 203-210 - [c7]James M. Hogan, Glenn Smith, Richard N. Thomas:
Tight Spirals and Industry Clients: The Modern SE Education Experience. ACE 2005: 217-222 - [c6]Andrew Marrington, James M. Hogan, Richard N. Thomas
:
Quality Assurance in a Student-Based Agile Software Engineering Process. Australian Software Engineering Conference 2005: 324-331 - [e2]Marcus Gallagher, James M. Hogan, Frédéric Maire:
Intelligent Data Engineering and Automated Learning - IDEAL 2005, 6th International Conference, Brisbane, Australia, July 6-8, 2005, Proceedings. Lecture Notes in Computer Science 3578, Springer 2005, ISBN 3-540-26972-X [contents] - 2004
- [c5]James M. Hogan, Chris Ho-Stuart, Bihn Pham:
Key Challenges in Software Internationalisation. ACSW 2004: 187-194 - [c4]Tony R. Sahama, Chris Ho-Stuart, James M. Hogan:
Developing and Delivering a Software Internationalisation Subject. ACSW 2004: 199-204 - [e1]James M. Hogan, Paul Montague, Martin K. Purvis, Chris Steketee:
ACSW Frontiers 2004, 2004 ACSW Workshops - the Australasian Information Security Workshop (AISW2004), the Australasian Workshop on Data Mining and Web Intelligence (DMWI2004), and the Australasian Workshop on Software Internationalisation (AWSI2004) . Dunedin, New Zealand, January 2004. CRPIT 32, Australian Computer Society 2004, ISBN 1-920682-14-7 [contents] - 2002
- [b1]James M. Hogan:
Recruitment learning in randomly connected neural networks. Queensland University of Technology, Brisbane, Australia, dissertation.de 2002, ISBN 978-3-89825-514-1, pp. 1-323 - [j5]James M. Hogan:
Advanced mean field methods: theory and practice: M. Opper and D. Saad (Eds.); MIT Press, Cambridge, MA, 2001, 300pp. ISBN 0-262-15054-9. Neurocomputing 48(1-4): 1057-1060 (2002) - [c3]James M. Hogan, Glenn Smith, Richard N. Thomas
:
The Real World Software Process. APSEC 2002: 366-375 - [c2]Jaspar Cahill, James M. Hogan, Richard N. Thomas
:
The Java Metrics Reporter- An Extensible Tool for 00 Software Analysis. APSEC 2002: 507-516 - 2001
- [j4]James M. Hogan, Joachim Diederich:
Recruitment Learning Of Boolean Functions In Sparse Random Networks. Int. J. Neural Syst. 11(6): 537-559 (2001)
1990 – 1999
- 1998
- [c1]James M. Hogan, Joachim Diederich, Gerard D. Finn:
Selective Attention and the Acquisition of Spatial Semantics. CoNLL 1998: 235-244 - 1997
- [j3]James M. Hogan, Peter C. J. James:
Australian Approaches to Internet Content Regulation. Aust. Comput. J. 29(1): 16-23 (1997) - 1993
- [j2]Helen A. Bergen, James M. Hogan:
A chosen plaintext attack on an adaptive arithmetic coding compression algorithm. Comput. Secur. 12(2): 157-167 (1993) - 1992
- [j1]Helen A. Bergen, James M. Hogan:
Data security in a fixed-model arithmetic coding compression algorithm. Comput. Secur. 11(5): 445-461 (1992)
Coauthor Index
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