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Analysis of combinatory algorithms

W. D. Frazer
1971 Proceedings of the November 16-18, 1971, fall joint computer conference on - AFIPS '71 (Fall)  
," viz., Analysis of a Analysis of a Class of Single Algorithm Algorithms Analysis of a Single Case (usually worst or best) Analysis of a Prob-1 --------+ ------1 ability Distribution of Cases The kinds  ...  SUMMARY In this brief space, it has of course been impossible to do justice to even the nascent field of combinatory algorithm analysis.  ... 
doi:10.1145/1478873.1478937 dblp:conf/afips/Frazer72 fatcat:gzf2n3gd2bf3hnrvxh7d6qypru

Combinatorial and Algorithmic Issues for Microarray Analysis [chapter]

Michael Langston, Carlos Cotta, Pablo Moscato
2007 Handbook of Approximation Algorithms and Metaheuristics  
Contrary to the current folkloric belief in combinatorial optimization, the method allows to solve to optimality large instances [3].  ...  ALGORITHMS 5 on an edge joining a pair of vertices.  ...  In addition, we will show how a memetic algorithm, using a similarity measure between pairs of genes (or pairs of samples), is able to obtain permutations of the rows and colums such that the final layout  ... 
doi:10.1201/9781420010749.ch74 fatcat:sofynppd4vdiplczydemkrg6be

Runtime Analysis of an Evolutionary Algorithm for Stochastic Multi-Objective Combinatorial Optimization

Walter J. Gutjahr
2012 Evolutionary Computation  
This may be a starting point for the runtime analysis of evolutionary SMOCO algorithms.  ...  For stochastic multi-objective combinatorial optimization (SMOCO) problems, the Adaptive Pareto Sampling (APS) framework has been proposed, which is based on sampling and on solution of deterministic multi-objective  ...  The author thanks Lothar Thiele for a discussion on -dominance concepts during the Dagstuhl seminar 2010 on "Theory of Evolutionary Algorithms", and three anonymous  ... 
doi:10.1162/evco_a_00050 pmid:22004001 fatcat:gwxhpnyecvdptjkdapskw2m4i4

Combinatorial Analysis of Multiple Networks [article]

Matteo Magnani, Barbora Micenkova, Luca Rossi
2013 arXiv   pre-print
In this work we introduce a real-world layered network combining different kinds of online and offline relationships, and present an innovative methodology and related analysis tools suggesting the existence  ...  We also introduce a notion of betweenness centrality for multiple networks.  ...  This leads to a discussion of future directions concerning both methodological issues and collection of new datasets.  ... 
arXiv:1303.4986v1 fatcat:qnynofjkgnbtdlnow53a5m2vte

Identification of a prognostic signature in colorectal cancer using combinatorial algorithm‐driven analysis

Abdo Alnabulsi, Tiehui Wang, Wei Pang, Marius Ionescu, Stephanie G Craig, Matthew P Humphries, Kris McCombe, Manuel Salto Tellez, Ayham Alnabulsi, Graeme I Murray
2022 The Journal of Pathology: Clinical Research  
Using a large dataset of immunohistochemistry-based biomarkers (n = 66), this study has developed an effective methodology for identifying optimal biomarker combinations as a prognostic tool.  ...  Biomarkers were screened and assigned to related subsets before being analysed using an iterative algorithm customised for evaluating combinatorial interactions between biomarkers based on their combined  ...  Acknowledgements The colorectal cancer microarray was provided by the NHS Grampian Biorepository and the majority of the immunostaining was performed in the Grampian Biorepository laboratory (www.biorepository  ... 
doi:10.1002/cjp2.258 pmid:35043584 pmcid:PMC8977276 fatcat:h3bhr6xgofawjk4iztizpzwqry

Differential analysis of combinatorial protein complexes with CompleXChange

Thorsten Will, Volkhard Helms
2019 BMC Bioinformatics  
a condition-specific manner for a sizeable number of samples, but not their assemblies.  ...  Here, we present a pipeline for differential analysis of protein complexes based on predicted or manually assigned complexes and inferred complex abundances, which can be easily applied on a whole-genome  ...  Acknowledgements We thank Michael Hutter and Nicolas Künzel for a careful reading of the manuscript.  ... 
doi:10.1186/s12859-019-2852-z fatcat:cmlu32leqvdbfcyty4d54jitqu

Combinatorial Data Analysis

P Arabie
1992 Annual Review of Psychology  
A closely related problem of da ta analysis, often omitted in surveys of methodology because of its nonprobabilistic basis, is the following : Devise a set of binary vectors or keys for optimally and parsimoniously  ...  Methodological contributions from combinatorial data analysis to this sub stantive area include hierarchical clustering (Corpet 19 88), additive trees (Dress et al 1986), computational complexity (Day  ...  ., Heiser, W. 1977 A preliminary study of optimal variable weighting in k-means clustering. J. Classif.  ... 
doi:10.1146/annurev.psych.43.1.169 fatcat:rnxxyygbi5ah3bdw3ahskl5hda

Sharp bounds on the runtime of the (1+1) EA via drift analysis and analytic combinatorial tools

Hsien-Kuei Hwang, Carsten Witt
2019 Proceedings of the 15th ACM/SIGEVO Conference on Foundations of Genetic Algorithms - FOGA '19  
The same approach proposed there also leads to a full asymptotic expansion with errors of the form O(n −K log n) for any K > 0.  ...  from well-established techniques for the running time analysis of evolutionary computation such as drift analysis.  ...  First, from a more didactical and methodological point of view, one may look for a more elementary derivation of the formula (1), at least with respect to the linear term −C 1 n.  ... 
doi:10.1145/3299904.3340302 dblp:conf/foga/HwangW19 fatcat:rakyfpt66vgedkimujqx4g7ejm

Combinatorial Data Analysis

P Arabie, L J Hubert
1992 Annual Review of Psychology  
A closely related problem of da ta analysis, often omitted in surveys of methodology because of its nonprobabilistic basis, is the following : Devise a set of binary vectors or keys for optimally and parsimoniously  ...  Methodological contributions from combinatorial data analysis to this sub stantive area include hierarchical clustering (Corpet 19 88), additive trees (Dress et al 1986), computational complexity (Day  ...  ., Heiser, W. 1977 A preliminary study of optimal variable weighting in k-means clustering. J. Classif.  ... 
doi:10.1146/annurev.ps.43.020192.001125 fatcat:y3sl23537fbljl243uv3jbn6ca

Conundrum of combinatorial complexity

L.I. Perlovsky
1998 IEEE Transactions on Pattern Analysis and Machine Intelligence  
These problems are manifested as combinatorial complexity of algorithms, of their computational or training requirements.  ...  The potential role of the fuzzy logic in overcoming current difficulties is discussed. Current mathematical difficulties are related to philosophical debates of the past.  ...  "Much of our current models and methodologies do not seem to scale out of limited 'toy' domains" [31] . The key issue is the "combinatorial explosion inherent in the problem" [16] .  ... 
doi:10.1109/34.683784 fatcat:adsjbg3n7rd5vmz7b3dhefelqe

Combinatorial Data Analysis [chapter]

L.J. Hubert, P. Arabie
2001 International Encyclopedia of the Social & Behavioral Sciences  
A closely related problem of da ta analysis, often omitted in surveys of methodology because of its nonprobabilistic basis, is the following : Devise a set of binary vectors or keys for optimally and parsimoniously  ...  Methodological contributions from combinatorial data analysis to this sub stantive area include hierarchical clustering (Corpet 19 88), additive trees (Dress et al 1986), computational complexity (Day  ...  ., Heiser, W. 1977 A preliminary study of optimal variable weighting in k-means clustering. J. Classif.  ... 
doi:10.1016/b0-08-043076-7/00651-3 fatcat:i4l5oislgbe57dzaqxcvbay5oi

Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis

L. Lancashire, O. Schmid, H. Shah, G. Ball
2005 Bioinformatics  
A subset of ions were identified that allowed for the consistent identification of species, classifying >97% of a separate validation subset of samples into their respective groups.  ...  Motivation: Robust computer algorithms are required to interpret the vast amounts of proteomic data currently being produced and to generate generalized models which are applicable to 'real world' scenarios  ...  Figure 1 shows a summary of the methodology used in the analysis.  ... 
doi:10.1093/bioinformatics/bti368 pmid:15746279 fatcat:pnmhi43kcjdu7aha6la2w2k75e

Dynamic combinatorial optimisation problems: an analysis of the subset sum problem

Philipp Rohlfshagen, Xin Yao
2010 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
These novel algorithms are subsequently evaluated on a wide range of different optimisation problems, including wellspecified benchmark generators.  ...  However, due to a lack of theoretical results, as well as a general lack of references to actual real-world scenarios, it is not entirely clear whether these benchmarks capture any of the characteristics  ...  EP/E058884/1 entitled ''Evolutionary Algorithms for Dynamic Optimisation Problems: Design, Analysis and Applications''.  ... 
doi:10.1007/s00500-010-0616-9 fatcat:utwlvqk5ezcndm4zxfqg6gnvvm

Identifying regulatory networks by combinatorial analysis of promoter elements

Yitzhak Pilpel, Priya Sudarsanam, George M. Church
2001 Nature Genetics  
Few studies, however, address the combinatorial nature of transcription, a well-established phenomenon in eukaryotes.  ...  The maps are highly connected, suggesting that a small number of transcription factors are responsible for a complex set of expression patterns in diverse conditions.  ...  Hughes for providing many of the motifs used in these analyses and U. Keich for assistance with the statistical analyses of motif synergies. We are grateful to J. Aach  ... 
doi:10.1038/ng724 pmid:11547334 fatcat:zften7cunzgh7hr2fwkyz73z4i

Breast cancer prognosis by combinatorial analysis of gene expression data

Gabriela Alexe, Sorin Alexe, David E Axelrod, Tibérius O Bonates, Irina I Lozina, Michael Reiss, Peter L Hammer
2006 Breast Cancer Research  
Moreover, the LAD model provides valuable insights into the roles of individual and combinatorial biomarkers, allows the discovery of new classes of patients, and generates a vast library of biomedical  ...  An extensive list of 'patterns' or 'combinatorial biomarkers' (that is, combinations of genes and limitations on their expression levels) was generated, and 40 patterns were used to create a prognostic  ...  The present study uses LAD, a combinatorics, optimization, and logic based methodology for the analysis of data.  ... 
doi:10.1186/bcr1512 pmid:16859500 pmcid:PMC1779471 fatcat:ctrmonl5ibh2hmu7vbatzv3opy
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