Computing and Information Systems - Research Publications
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ItemOn the reliability and the limits of inference of amino acid sequence alignments(OXFORD UNIV PRESS, 2022-06-24)MOTIVATION: Alignments are correspondences between sequences. How reliable are alignments of amino acid sequences of proteins, and what inferences about protein relationships can be drawn? Using techniques not previously applied to these questions, by weighting every possible sequence alignment by its posterior probability we derive a formal mathematical expectation, and develop an efficient algorithm for computation of the distance between alternative alignments allowing quantitative comparisons of sequence-based alignments with corresponding reference structure alignments. RESULTS: By analyzing the sequences and structures of 1 million protein domain pairs, we report the variation of the expected distance between sequence-based and structure-based alignments, as a function of (Markov time of) sequence divergence. Our results clearly demarcate the 'daylight', 'twilight' and 'midnight' zones for interpreting residue-residue correspondences from sequence information alone. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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ItemNo Preview AvailableBallot-Polling Audits of Instant-Runoff Voting Elections with a Dirichlet-Tree Model(Springer International Publishing, 2023-01-01)
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ItemUniversal Architectural Concepts Underlying Protein Folding Patterns(FRONTIERS MEDIA SA, 2021-04-30)What is the architectural "basis set" of the observed universe of protein structures? Using information-theoretic inference, we answer this question with a dictionary of 1,493 substructures-called concepts-typically at a subdomain level, based on an unbiased subset of known protein structures. Each concept represents a topologically conserved assembly of helices and strands that make contact. Any protein structure can be dissected into instances of concepts from this dictionary. We dissected the Protein Data Bank and completely inventoried all the concept instances. This yields many insights, including correlations between concepts and catalytic activities or binding sites, useful for rational drug design; local amino-acid sequence-structure correlations, useful for ab initio structure prediction methods; and information supporting the recognition and exploration of evolutionary relationships, useful for structural studies. An interactive site, Proçodic, at http://lcb.infotech.monash.edu.au/prosodic (click), provides access to and navigation of the entire dictionary of concepts and their usages, and all associated information. This report is part of a continuing programme with the goal of elucidating fundamental principles of protein architecture, in the spirit of the work of Cyrus Chothia.
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ItemLightweight Nontermination Inference with CHCs(SPRINGER INTERNATIONAL PUBLISHING AG, 2021)Non-termination is an unwanted program property (considered a bug) for some software systems, and a safety property for other systems. In either case, automated discovery of preconditions for non-termination is of interest. We introduce NtHorn, a fast lightweight non-termination analyser, able to deduce non-trivial sufficient conditions for non-termination. Using Constrained Horn Clauses (CHCs) as a vehicle, we show how established techniques for CHC program transformation and abstract interpretation can be exploited for the purpose of non-termination analysis. NtHorn is comparable in power to the state-of-the-art non-termination analysis tools, as measured on standard competition benchmark suites (consisting of integer manipulating programs), while typically solving problems an order of magnitude faster.
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ItemDisjunctive Interval Analysis(SPRINGER INTERNATIONAL PUBLISHING AG, 2021)We revisit disjunctive interval analysis based on the Boxes abstract domain. We propose the use of what we call range decision diagrams (RDDs) to implement Boxes, and we provide algorithms for the necessary RDD operations. RDDs tend to be more compact than the linear decision diagrams (LDDs) that have traditionally been used for Boxes. Representing information more directly, RDDs also allow for the implementation of more accurate abstract operations. This comes at no cost in terms of analysis efficiency, whether LDDs utilise dynamic variable ordering or not. RDD and LDD implementations are available in the Crab analyzer, and our experiments confirm that RDDs are well suited for disjunctive interval analysis.
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ItemNo Preview AvailableA Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks over Multiple Time Periods(INFORMS (Institute for Operations Research and Management Sciences), 2016)We consider the multiple-time-period, short-term production scheduling problem for a network of multiple open-pit mines and ports. Ore produced at each mine, in each period, is transported by rail to a set of ports and blended into products for shipping. Each port forms these blends to a specification, as stipulated in contracts with downstream customers. This problem belongs to a class of multiple producer/consumer scheduling problems in which producers are able to generate a range of products, a combination of which are required by consumers to meet specified demands. In practice, short-term schedules are formed independently at each mine, tasked with achieving a grade and quality target outlined in a medium-term plan. Because of uncertainty in the data available to a medium-term planner and the dynamics of the mining environment, such targets may not be feasible in the short term. In this paper, we present an algorithm in which the grade and quality targets assigned to each mine are iteratively adapted, ensuring the satisfaction of blending constraints at each port while generating schedules for each mine that maximise resource utilisation. This paper was accepted by Yinyu Ye, optimization.
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ItemNo Preview AvailableSequencing operator counts(AAAI Press, 2016-01-01)Copyright 2016 AAAI, all rights reserved.). Operator-counting is a recently developed framework for analysing and integrating many state-ofthe- art heuristics for planning using Linear Programming. In cost-optimal planning only the objective value of these heuristics is traditionally used to guide the search. However the primal solution, i.e. the operator counts, contains useful information. We exploit this information using a SATbased approach which given an operator-count, either finds a valid plan; or generates a generalized landmark constraint violated by that count. We show that these generalized landmarks can be used to encode the perfect heuristic, h∗, as a Mixed Integer Program. Our most interesting experimental result is that finding or refuting a sequence for an operator-count is most often empirically efficient, enabling a novel and promising approach to planning based on Logic-Based Benders Decomposition (LBBD). This paper originally appeared at ICAPS 2015 and is reproduced with the permission of the Association for Artificial Intelligence ([Davies et al., 2015]
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ItemNo Preview AvailableMulti-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm(TAYLOR & FRANCIS LTD, 2018-12-02)This article presents a novel algorithm for solving a short-term open-pit production-scheduling problem in which several objectives, of varying priority, characterize the quality of each solution. A popular approach employs receding horizon control, dividing the horizon into N period-aggregates of increasing size (number of periods or span). An N-period mixed integer program (MIP) is solved for each period in the original horizon to incrementally construct a production schedule one period at a time. This article presents a new algorithm that, in contrast, decomposes the horizon into N period-aggregates of equal size. Given a schedule for these N periods, obtained by solving an N-period MIP, the first of these aggregates is itself decomposed into an N-period scheduling problem with guidance provided on what regions of the mine should be extracted. The performance of this hierarchical decomposition-based approach is compared with that of receding horizon control on a suite of data sets generated from an operating mine producing millions of tons of ore annually. As the number of objectives being optimized increases, the hierarchical decomposition-based algorithm outperforms receding horizon control, in a majority of instances.
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ItemNo Preview AvailableShort-term planning for open pit mines: a review(TAYLOR & FRANCIS LTD, 2019-07-04)This review examines the current state-of-the-art in short-term planning for open-pit mines, with a granularity that spans days, weeks or months, and a horizon of less than one to two years. In the academic literature, the short-term planning problem for open-pit mines has not been as widely considered as that for the medium- and long-term horizons. We highlight the differences between short- and longer term planning in terms of both the level of detail to which a mine site is modelled, and the objectives that are optimised when making decisions. We summarise the range of techniques that have been developed for generating short-term plans, capturing both mathematical programming-based methods and heuristic approaches using local-search and decomposition. We identify key challenges and future directions in which to advance the state-of-the-art in short-term planning for open-pit mines.
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ItemAbstract Interpretation over Non-Lattice Abstract Domains(Springer, 2013)The classical theoretical framework for static analysis of programs is abstract interpretation. Much of the power and elegance of that framework rests on the assumption that an abstract domain is a lattice. Nonetheless, and for good reason, the literature on program analysis provides many examples of non-lattice domains, including non-convex numeric domains. The lack of domain structure, however, has negative consequences, both for the precision of program analysis and for the termination of standard Kleene iteration. In this paper we explore these consequences and present general remedies.