Hui Kian Ho
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Hui Kian Ho has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Ramamohanarao Kotagiri
Department of Computing and Information Systems, The University of Melbourne, Victoria, 3010, Australia
2 shared publications - Graeme Gange
Monash University
1 shared publication - Michael J. Kuiper
Victorian Life Sciences Computation Initiative, the University of Melbourne,Parkville Campus, 187 Grattan Street, Carlton, VIC 3010, Australia
1 shared publication - Michael Kuiper
Australian AI Safety Institute, Department of Industry, Science and Resources, Canberra, ACT, Australia
1 shared publication
Latest Publications
- Open Access
- 30 July 2012
- Published by Springer Nature in BMC Research Notes
- Vol. 5 (1) , 391
BetaSearch: a new method for querying β-residue motifs
Searching for structural motifs across known protein structures can be useful for identifying unrelated proteins with similar function and characterising secondary structures such as β-sheets. This is infeasible using conventional sequence alignment because linear protein sequences do not contain spatial information. β-residue motifs are β-sheet substructures that can be represented as graphs and queried using existing graph indexing methods, however, these approaches are designed for general graphs that do not incorporate the inherent structural constraints of β-sheets and require computationally-expensive filtering and verification procedures. 3D substructure search methods, on the other hand, allow β-residue motifs to be queried in a three-dimensional context but at significant computational costs.
- 30 July 2012
- Published by Springer Nature in BMC Research Notes
- Vol. 5 (1) , 391
Open AccessBetaSearch: a new method for querying β-residue motifs
Searching for structural motifs across known protein structures can be useful for identifying unrelated proteins with similar function and characterising secondary structures such as β-sheets. This is infeasible using conventional sequence alignment because linear protein sequences do not contain spatial information. β-residue motifs are β-sheet substructures that can be represented as graphs and queried using existing graph indexing methods, however, these approaches are designed for general graphs that do not incorporate the inherent structural constraints of β-sheets and require computationally-expensive filtering and verification procedures. 3D substructure search methods, on the other hand, allow β-residue motifs to be queried in a three-dimensional context but at significant computational costs.
- Open Access
- 31 October 2008
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 24 (24) , 2934-2935
PConPy—a Python module for generating 2D protein maps
Summary: PConPy is an open-source Python module for generating protein contact maps, distance maps and hydrogen bond plots. These maps can be generated in a number of publication-quality vector and raster image formats. Contact maps can be annotated with secondary structure and hydrogen bond assignments. PConPy offers a more flexible choice of contact definition parameters than existing toolkits, most notably a greater choice of inter-residue distance metrics. PConPy can be used as a stand-alone application or imported into existing source code. A web-interface to PConPy is also available for use. Availability: The PConPy web-interface and source code can be accessed from its website at http://www.csse.unimelb.edu.au/~hohkhkh1/pconpy/. Contact:hohkhkh1@csse.unimelb.edu.au Supplementary information:Supplementary data are available at Bioinformatics online.
- 31 October 2008
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 24 (24) , 2934-2935
Open AccessPConPy—a Python module for generating 2D protein maps
Summary: PConPy is an open-source Python module for generating protein contact maps, distance maps and hydrogen bond plots. These maps can be generated in a number of publication-quality vector and raster image formats. Contact maps can be annotated with secondary structure and hydrogen bond assignments. PConPy offers a more flexible choice of contact definition parameters than existing toolkits, most notably a greater choice of inter-residue distance metrics. PConPy can be used as a stand-alone application or imported into existing source code. A web-interface to PConPy is also available for use. Availability: The PConPy web-interface and source code can be accessed from its website at http://www.csse.unimelb.edu.au/~hohkhkh1/pconpy/. Contact:hohkhkh1@csse.unimelb.edu.au Supplementary information:Supplementary data are available at Bioinformatics online.