Publications

• S. Rajapaksa, L. Allison, P. J. Stuckey, M. Garcia de la Banda, A. S. Konagurthu, The divergence time of protein structures modelled by Markov matrices and its relation to the divergence of sequences, arxiv:2308.06292, August 2023.
• P. R. Amarasinghe, L. Allison, P. J. Stuckey, M. Garcia de la Banda, A. M. Lesk, A. S. Konagurthu, Getting 'φψχal' with proteins: minimum message length inference of joint distributions of backbone and sidechain dihedral angles, Bioinformatics, 39(s.1), pp.i357-i367, doi:10.1093/bioinformatics/btad251, June 2023.
• D. Sumanaweera, L. Allison, A. S. Konagurthu, Bridging the Gaps in Statistical Models of Protein Alignment, Bioinformatics, 38(s1) pp.i229-i237, doi:10.1093/bioinformatics/btac246, July 2022.
• S. Rajapaksa, D. Sumanaweera, A. M. Lesk, L. Allison, P. Stuckey, M. Garcia de la Banda, P. Stuckey, D. Abramson, A. S. Konagurthu, On the Reliability and Limits of Protein Sequence Alignments, Bioinformatics, 38(s1), pp.i255-i263, doi:10.1093/bioinformatics/btac247, July 2022.
• Lloyd Allison, Subclasses of Class Function used to Implement Transformations of Statistical Models, arxiv:2207.04218, July 2022.
• Sandun Rajapaksa, Dinithi Sumanaweera, Maria Garcia de la Banda, Peter Stuckey, David Abramson, Lloyd Allison, Arthur Lesk, Arun Konagurthu, On identifying statistical redundancy at the level of amino acid subsequences, IEEE Int. Conf. on Bioinformatics and Biomedicine (BIBM), pp.64-71, doi:10.1109/BIBM52615.2021.9669282, 9-12 December 2021.
• Rodney T. O'Donnell, Kevin B. Korb, Lloyd Allison, Causal KL: Evaluating Causal Discovery, arXiv:2111.06029, 11 November 2021. (Also TR 207, FIT, Monash University, February 2007.)
• Yang Li, Lloyd Allison and Kevin B. Korb The Difficulty of Being Moral, Theoretical Computer Science, vol.885, pp.77-90, doi:10.1016/j.tcs.2021.06.024, 11 September 2021.
• Arun S. Konagurthu, Ramanan Subramanian, Lloyd Allison, David Abramson, Peter J. Stuckey, Maria Garcia De La Banda and Arthur M. Lesk, Universal architectural concepts underlying protein folding patterns, Frontiers in Molecular Biosciences, special issue 'A Journey Through 50 Years of Structural Bioinformatics in Memoriam of Cyrus Chothia.' doi:10.3389/fmolb.2020.612920, 30 April 2021 (Also see [prosodic].)
• Lloyd Allison, Arun S. Konagurthu, Daniel F. Schmidt, On Universal Codes for Integers: Wallace Tree, Elias Omega and Beyond, IEEE, Data Compression Conference (DCC), doi:10.1109/DCC50243.2021.00039, pp.313-322, 22-26 March 2021. (Also see AKS 2019.)
• A. M. Lesk, A. S. Konagurthu, L. Allison, M. Garcia de la Banda, P. J. Stuckey and D. Abramson, Computer modelling of a potential agent against SARS-Cov-2 (COVID-19) protease, Proteins: Structure, Function and Bioinformatics, 88(12), pp.1557-1558, July 2020.
  
  
• Dinithi Sumanaweera, Lloyd Allison, Arun Konagurthu, Statistical Compression of Protein Sequences and Inference of Marginal Probability Landscapes over Competing Alignments using Finite State Models and Dirichlet Priors, Bioinformatics, 35(14), pp.i360-i369, doi:10.1093/bioinformatics/btz368, 5 July 2019, and Proc. of 27th ISMB & 18th ECCB, July 2019.
• Lloyd Allison, Arun Konagurthu and Daniel Schmidt, On universal codes for integers: Wallace Tree, Elias Omega and variations, arXiv:1906.05004, June 2019.
• A. S. Konagurthu, R. Subramanian, L. Allison, D. Abramson, M. Garcia de la Banda, P. Stuckey, A. M. Lesk, Information-Theoretic Inference of an Optimal Dictionary of Protein Supersecondary Structures, in 'Protein Supersecondary Structures', Springer, Methods in Molecular Biology (MIMB) vol.1958, pp.123-131, doi:10.1007/978-1-4939-9161-7_6, April 2019.
• Lloyd Allison, Coding Ockham's Razor, Springer, doi: 10.1007/978-3-319-76433-7, 2018 — implementing Minimum Message Length (MML) software for inductive inference. Also see the [mmlist].
• Dinithi Sumanaweera, Lloyd Allison, and Arun S. Konagurthu, The bits between proteins, IEEE, Data Compression Conference (DCC), doi:10.1109/DCC.2018.00026, pp.177-186, 26-30 March 2018.
• Ramanan Subramanian, Lloyd Allison, Peter J. Stuckey, Maria Garcia de la Banda, David Abramson, Arthur M. Lesk and Arun S. Konagurthu, Statistical compression of protein folding patterns for inference of recurrent substructural themes, IEEE, Data Compression Conference (DCC), doi:10.1109/DCC.2017.46, pp.340-349, 4-7 April 2017.
• James H. Collier, Lloyd Allison, Arthur M. Lesk, Peter J. Stuckey, Maria Garcia de la Banda and Arun S. Konagurthu, Statistical inference of protein structural alignments using information and compression, Bioinformatics, 33(7), pp.1005-1013, doi:10.1093/bioinformatics/btw757, (online January) April 2017.
• Minh Duc Cao, Lloyd Allison, Trevor I. Dix and Mikael Boden, Robust estimation of evolutionary distances with information theory, J. Molecular Biology and Evolution, 33(5), doi:10.1093/molbev/msw019, pp.1349-1357, (online 23 February) 1 May 2016.
• A. S. Konagurthu, P. Kasarapu, L. Allison, J. H. Collier and A. M. Arthur, On sufficient statistics of least-squares superposition of vector sets, J. Comp. Biol., 22(6), pp.487-497, May 2015.
• Parthan Kasarapu, Lloyd Allison, Minimum message length estimation of mixtures of multivariate Gaussian and von Mises-Fisher distributions, Machine Learning, 100(2), pp.333-378, doi:10.1007/s10994-015-5493-0,  March 2015.
• Arun S. Konagurthu, Parthan Kasarapu, Lloyd Allison, James H. Collier and Arthur M. Lesk, On Sufficient Statistics of Least-Squares Superposition of Vector Sets, RECOMB 2014, Springer Verlag, LNBI 8394, pp.144-159, 2014.
• F. Petitjean, L. Allison and G. I. Webb, A statistically efficient and scalable method for log-linear analysis of high-dimensional data, International Conference on Data Mining (ICDM 2014).
• Lloyd Allison. On the complexity of graphs (networks) by information content, and conditional (mutual) information given other graphs, TR #2014/277, Faculty of Information Technology, Monash University, 2014.
• James H. Collier, Lloyd Allison, Arthur M. Lesk, Maria Garcia de la Banda and Arun S. Konagurthu, A new statistical framework to assess structural alignment quality using information compression, ECCB) J. Bioinformatics, 30(17), pp.i512-i518, September 2014.
• Arun Konagurthu, Lloyd Allison, David Abramson, Peter Stuckey and Arthur Lesk, How precise are reported protein coordinate data? Acta Cryst., D70(3), pp.904-906, March 2014.
• Arun S. Konagurthu, Lloyd Allison, David Abramson, Peter J. Stuckey, Arthur M. Lesk, Statistical Inference of Protein "LEGO Bricks", International Conference on Data Mining (ICDM 2013), Dallas, Texas, USA, 7-10 December 2013.
• Enes Makalic, Lloyd Allison, MMLD Inference of Multiplayer Perceptrons, in Algorithmic Probability and Friends: Bayesian Prediction and Artificial Intelligence: Papers from the Ray Solomonoff 85th Memorial Conference (30 Nov.–2 Dec. 2011), Springer-Verlag, LNCS LNAI vol.7070, pp.261-272, doi:10.1007/978-3-642-44958-1_20, 2013.
• Arun S. Konagurthu, Arthur M. Lesk, Lloyd Allison, Minimum Message Length Inference of Secondary Structure from Protein Coordinate Data, Bioinformatics, 28(12), pp.i97-i105, doi:10.1093/bioinformatics/bts223,  June 2012 (ISMB, July 2012).
• Arun S. Konagurthu, Lloyd Allison, Peter J. Stuckey and Arthur M. Lesk, Piecewise linear approximation of protein structures using the principle of minimum message length, Bioinformatics, vol.27, no.13, pp.i43-i51, 2011, Proc. ISMB/ECCB, July 2011.
• Minh Duc Cao, Trevor I. Dix and Lloyd Allison, A Biological Compression Model and its Applications, in 'Software Tools and Algorithms for Biological Systems', Springer Verlag, Advances in Experimental Medicine and Biology (AEMB), vol.696, pp.657-666, April 2011.
• Arun Konagurthu, Lloyd Allison, Thomas Conway, Bryan Beresford-Smith and Justin Zobel, Design of an Efficient Out-of-Core Read Alignment Algorithm, WABI, Springer Verlag, LNCS/LNBI 6293, pp.189-201, 2010.
• Minh Duc Cao, Trevor I. Dix and Lloyd Allison, A Genome Alignment Algorithm Based on Compression, BMC Bioinformatics, 11:599, 2010.
  
  
• Minh Duc Cao, Trevor I. Dix and Lloyd Allison, A Genome Alignment Algorithm Based on Compression, TR #233, Faculty of Information Technology, Monash University, 2009.
• Minh Duc Cao, Trevor I. Dix and Lloyd Allison, Computing substitution matrices for genomic comparative analysis, Springer Verlag, LNCS 5476/2009, PAKDD09.
• M. D. Cao, L. Allison, T. I. Dix, A distance measure for genome phylogenetic analysis, Springer Verlag, LNCS 5866 (AI09), pp.71-80, December 2009.
• Lloyd Allison, Added Distributions for use in Clustering (Mixture Modelling), Function Models, Regression Trees, Segmentation, and mixed Bayesian Networks in Inductive Programming 1.2, TR 2008/224, FIT, Monash University, April 2008.
• Minh Duc Cao, Trevor I. Dix, Lloyd Allison, Chris Mears, A Simple Statistical Algorithm for Biological Sequence Compression, IEEE, Data Compression Conference (DCC), pp.43-52, doi:10.1109/DCC.2007.7,  2007.
• Trevor I. Dix, David R. Powell, Lloyd Allison, Julie Bernal, Samira Jaeger, Linda Stern, Comparative Analysis of Long DNA Sequences by Per Element Information Content Using Different Contexts, BMC Bioinformatics, 8(Suppl.2):S10, May 2007.
• M. B. Dale, L. Allison and P. E. R. Dale, Segmentation and Clustering as Complementary Sources of Information, Acta Oecologica, 31(2), pp.193-202, March-April 2007.
• Rodney T. O'Donnell, Lloyd Allison and Kevin B. Korb, Learning Hybrid Bayesian Networks by MML, AI2006, Springer Verlag, LNCS vol.4304, pp.192-203, 2006.
• Lloyd Allison, A Programming Paradigm for Machine Learning, with a Case Study of Bayesian Networks, ACSC2006, pp.103-111, January 2006.
• Lloyd Allison, Inductive Inference 1.1.2: Inductive Programming and a Case Study of Bayesian Networks, TR 2005/177, School of Computer Science and Software Engineering, Monash University, 2005.
• Lloyd Allison, Models for machine learning and data mining in functional programming, J. Functional Programming (JFP), 15(1), pp.15-32, doi:10.1017/S0956796804005301, January 2005.
• Lloyd Allison, Finding Approximate Palindromes in Strings Quickly and Simply, TR 2004/162, School of Computer Science and Software Engineering, Monash University, 2004.
• Enes Makalic, Lloyd Allison, Andrew Paplinski, MML inference of RBF neural networks for regression, Brazilian Symp. on Artificial Neural Networks (SBRN), IEEE and Brazillian Computer Soc., September 2004.
• David R. Powell, Lloyd Allison and Trevor I. Dix, Modelling-Alignment for Non-Random Sequences, AI2004, Springer Verlag, LNCS vol.3339, pp.203-214, doi:10.1007/978-3-540-30549-1_19,  2004.
• Lloyd Allison, Inductive Inference 1.1, TR 153, School of Computer Science and Software Engineering, Monash University, 2004.
• L. J. Fitzgibbon, L. Allison and J. W. Comley, Probability Model Type Sufficiency, International Conference on Intelligent Data Engineering and Automated Learning (IDEAL-2003), Hong Kong, 21-23 March 2003.
• J. W. Comley, L. Allison and L. J. Fitzgibbon, Flexible Decision Trees in a General Data-Mining Environment, International Conference on Intelligent Data Engineering and Automated Learning (IDEAL-2003), Hong Kong, 21-23 March 2003.
• L. J. Fitzgibbon, D. L. Dowe and L. Allison, Bayesian Posterior Comprehension via Message from Monte Carlo, Second Hawaii International Conference on Statistics and Related Fields, Hawaii, 5-8 June 2003.
• Lloyd Allison, The Types of Models, Second Hawaii International Conference on Statistics and Related Fields, 2003.
• L. Allison, Longest Biased Interval and Longest Non-Negative Sum Interval, Bioinformatics, 19(10), pp1294-1295, doi:10.1093/bioinformatics/btg135,  1 July 2003.
• Enes Makalic, Lloyd Allison and David L. Dowe, MML Inference of Single-Layer Neural Networks, 3rd International Conference on Artificial Intelligence and Applications, AIA, 2003.
• Lloyd Allison, Types and Classes of Machine Learning and Data Mining, Twenty-Sixth Australasian Computer Science Conference (ACSC2003), pp207-215, Adelaide, 2003.
• Lloyd Allison, Version 1.0: 200309 (TR 2003/148), 2003.
• Lloyd Allison, Model Classes, TR 2002/125, School of Computer Science and Software Engineering, Monash University, 2002.
• Leigh J. Fitzgibbon, David L. Dowe and Lloyd Allison, Change-Point Estimation Using New Minimum Message Length Approximations, Proc. Seventh Pacific Rim International Conference on Artificial Intelligence, August 18-22, 2002.
• Leigh J. Fitzgibbon, David L. Dowe and Lloyd Allison, Univariate Polynomial Inference by Monte Carlo Message Length Approximation, Nineteenth International Conference on Machine Learning (ICML), 2002.
• Linda Stern, Lloyd Allison, Ross L. Coppel and Trevor I. Dix, Discovering patterns in Plasmodium falciparum genomic DNA, Molecular and Biochemical Parasitology, 118(2), pp.175-186, 2001.
• L. Allison, D. Powell and T. I. Dix, Modelling Is More Versatile Than Shuffling, TR 2000/83, School of Computer Science and Software Engineering, Monash University, 2000.
• D. R. Powell, L. Allison and T. I. Dix, Fast, Optimal Alignment of Three Sequences Using Linear Gap Cost, Journal of Theoretical Biology, 207(3), pp.325-336, December 2000.
• Lloyd Allison, Generator and Search Objects in Java, Journal of Research and Practice in Information Technology, vol.32, no.1, February 2000.
• L. Allison, L. Stern, T. Edgoose and T.I. Dix, Sequence complexity for biological sequence analysis, Computers and Chemistry, vol.24(1), pp.43-55, 2000.
• L. J. Fitzgibbon, L. Allison and D. L. Dowe, Minimum message length grouping of ordered data, Proc. 11th Int. Workshop on Algorithmic Learning Theory (ALT 2000), Springer Verlag, LNCS 1968, 2000.
  
  
• D. R. Powell, L. Allison and T. I. Dix, A versatile divide and conquer technique for optimal string alignment, Information Processing Letters, 70(3) pp.127-139, 1999.
• L. Allison, D. Powell and T. I. Dix, Compression and Approximate Matching, The Computer Journal, Volume 42, Issue 1, pp.1-10, doi:10.1093/comjnl/42.1.1,  1999.
• T. Edgoose and L. Allison, MML Markov classification of sequential data, Stats. and Comp., 9(4), pp.269-278, September 1999.
• Glen Pringle, Lloyd Allison and David L. Dowe, What is a tall poppy among web pages? Proc. 7th Int. World Wide Web Conference, pp.369-377, April 1998.
• L. Allison, Information-Theoretic Sequence Alignment, TR 98/14, School of Computer Science and Software Engineering, Monash University, 1998.
• David R. Powell, David L. Dowe, Lloyd Allison and Trevor I. Dix, Discovering simple DNA sequences by compression, PSB, 1998.
• T. Edgoose, L. Allison, D. L. Dowe, An MML Classification of Protein Sequences that knows about Angles and Sequences, Pacific Symp. on Biocomputing (PSB), pp.585-596, January 1998.
• L. Allison, T. Edgoose, T. I. Dix, Compression of Strings with Approximate Repeats, Intelligent Systems in Molecular Biology (ISMB98), pp.8-16, Montreal, 28 June - 1 July, 1998.
• D. R. Powell, L. Allison, T. I. Dix and D. L. Dowe, Alignment of low information sequences, Proceedings of the Fourth Australasian Theory Symposium (CATS '98), February 1998.
• Tim Edgoose and Lloyd Allison, Minimum Message Length Hidden Markov Modelling, IEEE, Data Compression Conference (DCC), pp.169-178, 1998.
• D. L. Dowe, L. Allison, T. Dix, L. Hunter, C. S. Wallace, T. Edgoose, Circular Clustering of Protein Dihedral Angles by Minimum Message Length, Pacific Symp. on Biocomputing (PSB), 1996.
• L. Allison and C. S. Wallace, The Posterior Probability Distribution of Alignments and its Application to Parameter Estimation of Evolutionary Trees and to Optimisation of Multiple Alignments, Journal of Molec. Evol., 39(4), pp.418-430, doi:10.1007/BF00160274,  1994.
• L. Allison, Using Hirschberg's Algorithm to Generate Random Alignments of Strings, Information Processing Letters, 51(5), pp.251-255, September 1994.
• L. Allison and C. S. Wallace, An Information Measure for the String to String Correction Problem with Applications, ACSC-17, pp.659-668, 19-21 January 1994.
• A. Finlay and L. Allison, A correction to the denotational semantics for Prolog of Nicholson and Foo, ACM Trans. Prog. Langs. and Systems, 15(1), pp.206-208, January 1993.
• L. Allison, A Fast Algorithm for the Optimal Alignment of Three Strings, Journal of Theoretical Biology, 164(2), pp.261-269, September 1993.
• L. Allison, Normalization of Affine Gap Costs Used in Optimal Sequence Alignment, Journal of Theoretical Biology, 161(2), pp.263-269, March 1993.
• C. N. Yee and L. Allison, Reconstruction of Strings Past, Journal of Bioinformatics (was Comp. Appl. BioSci., CABIOS), 9(1), pp.1-7, February 1993.
• Lloyd Allison, Applications of Recursively Defined Data Structures, Australian Computer Journal, 25(1), pp.14-20, arxiv:2206.12795, 1993.
• David L. Dowe, Jonathan Oliver, Trevor I. Dix, Lloyd Allison and Christopher S. Wallace, A Decision Graph Explanation of Protein Secondary Structure Prediction, 26th Hawaii International Conference on Systems Sciences (HICSS26), vol.1, pp.669-678, January 1993.
• L. Allison, Lazy Dynamic-Programming can be Eager, Information Processing Letters, 43(4), pp.207-212, September 1992.
• L.Allison, C.S.Wallace and C.N.Yee, Finite-State Models in the Alignment of Macro-Molecules, Journal of Molec. Evol., 35(1), pp.77-89, doi:10.1007/BF00160262,  1992.
• L. Allison, C. S. Wallace and C. N. Yee, Minimum Message Length Encoding, Evolutionary Trees and Multiple-Alignment, Hawaii Int. Conf. Sys. Sci. 25, vol.1, pp.663-674, January 1992.
• L. Allison, T. I. Dix and C. N. Yee, Shortest Path and Closure Algorithms for Banded Matrices, Information Processing Letters, 40, pp.317-322, 30 Dec 1991.
• Shirley T. S. Ho , Lloyd Allison and Chut N. Yee, Restriction site mapping for three or more enzymes, J. Bioinformatics (was CABIOS), 6(3), pp.195-204, 1990.
• L. Allison and C. N. Yee, Minimum message length encoding and the comparison of macromolecules, Bulletin of Mathematical Biology, 52(3), pp.431-453, May 1990.
• L. Allison, Continuations Implement Generators and Streams, The Computer Journal, vol.33, no.5, pp.460-465, 1990.
• L. Allison, C. S. Wallace and C. N. Yee, When is a String Like a String? International Symposium on Artificial Intelligence and Mathematics (AIM), January 1990.
• L.Allison, C.S.Wallace and C.N.Yee, Inductive Inference over Macro-Molecules, TR 90/148, Department of Computer Science, Monash University, November 1990.
  
  
• Lloyd Allison, Circular Programs and Self-Referential Structures, Software Practice & Experience, 19(2), pp.99-109, doi:10.1002/spe.4380190202, arxiv:2403.01866, February 1989.
• Lloyd Allison, Direct semantics and exceptions define jumps and coroutines, Information Processing Letters, 31(6), pp.327-330, June 1989.
• C. McDonald and L. Allison, Denotational semantics of a command interpreter and their implementation in standard ML, The Computer Journal, Volume 32, Issue 5, pp.422-431, December 1989.
• L. Allison and C. N. Yee, Restriction Site Mapping is in Separation Theory, Nucleic Acids Research / Computer Applications in the Biosciences (CABIOS) special issue, CABIOS (now Jrnl of Bioinformatics), 4(1), pp.97-101, January 1988.
• L. Allison, Some Applications of Continuations, The Computer Journal, Volume 31, Issue 1, pp.9-16, 1988.
• Lloyd Allison, Exceptions, a mathematical semantics for handling full jumps, TR 87/90, Department of Computer Science, Monash University, March 1987.
• Lloyd Allison, A Practical Introduction to Denotational Semantics, Cambridge Univ. Press, doi:10.1017/CBO9781139171892, 1986.
• L. Allison and T.I. Dix, A Bit-String Longest-Common-Subsequence Algorithm, Information Processing Letters, vol.23, pp.305-310, doi:10.1016/0020-0190(86)90091-8,  December 1986.
• L. Allison, Programming Denotational Semantics II, The Computer Journal, vol.28, no.5, pp.480-486, 1985.
• Lloyd Allison, Stable Marriages by Coroutines, Information Processing Letters, 16(2), pp.61-65, February 1983.
• Lloyd Allison, Programming Denotational Semantics, The Computer Journal, vol.26, no.2, pp.164-174, 1983.
• Lloyd Allison, An executable Prolog semantics, Algol Bulletin, vol.50, pp.10-18, December 1983.
• Lloyd Allison, Generating Coset Representatives for Permutation Groups, J. Algorithms, 2, pp.227-244, September 1981.
  
  
• Lloyd Allison, Phrase Structures, Non-Determinism and Backtracking, Information Processing Letters, 7(3), pp.139-143, April 1978.

That's most of them. (orcid id [0000-0002-9020-3164])