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Algorithms for Molecular Biology: AMB

Timo Beller, Enno Ohlebusch
[This corrects the article DOI: 10.1186/s13015-016-0083-7.].
2016: Algorithms for Molecular Biology: AMB
S Srivastava, S B Lal, D C Mishra, U B Angadi, K K Chaturvedi, S N Rai, A Rai
BACKGROUND: Protein structure comparison play important role in in silico functional prediction of a new protein. It is also used for understanding the evolutionary relationships among proteins. A variety of methods have been proposed in literature for comparing protein structures but they have their own limitations in terms of accuracy and complexity with respect to computational time and space. There is a need to improve the computational complexity in comparison/alignment of proteins through incorporation of important biological and structural properties in the existing techniques...
2016: Algorithms for Molecular Biology: AMB
Jun Zhou, Yu Lin, Vaibhav Rajan, William Hoskins, Bing Feng, Jijun Tang
BACKGOUND: Evolution of cancer cells is characterized by large scale and rapid changes in the chromosomal  landscape. The fluorescence in situ hybridization (FISH) technique provides a way to measure the copy numbers of preselected genes in a group of cells and has been found to be a reliable source of data to model the evolution of tumor cells. Chowdhury et al. (Bioinformatics 29(13):189-98, 23; PLoS Comput Biol 10(7):1003740, 24) recently develop a computational model for tumor progression driven by gains and losses in cell count patterns obtained by FISH probes...
2016: Algorithms for Molecular Biology: AMB
Ricardo Andrade, Martin Wannagat, Cecilia C Klein, Vicente Acuña, Alberto Marchetti-Spaccamela, Paulo V Milreu, Leen Stougie, Marie-France Sagot
BACKGROUND: What an organism needs at least from its environment to produce a set of metabolites, e.g. target(s) of interest and/or biomass, has been called a minimal precursor set. Early approaches to enumerate all minimal precursor sets took into account only the topology of the metabolic network (topological precursor sets). Due to cycles and the stoichiometric values of the reactions, it is often not possible to produce the target(s) from a topological precursor set in the sense that there is no feasible flux...
2016: Algorithms for Molecular Biology: AMB
Jerome Ambroise, Jamal Badir, Louise Nienhaus, Annie Robert, Anne-France Dekairelle, Jean-Luc Gala
BACKGROUND: Pyrosequencing Allele Quantification (AQ) is a cost-effective DNA sequencing method that can be used for detecting somatic mutations in formalin-fixed paraffin-embedded (FFPE) samples. The method displays a low turnaround time and a high sensitivity. Pyrosequencing suffers however from two main drawbacks including (i) low specificity and (ii) difficult signal interpretation when multiple mutations are reported in a hotspot genomic region. RESULTS: Using a constraint-based regression method, the new AdvISER-PYRO-SMQ algorithm was developed in the current study and implemented into an R package...
2016: Algorithms for Molecular Biology: AMB
Rui Henriques, Sara C Madeira
BACKGROUND: Biclustering has been largely used in biological data analysis, enabling the discovery of putative functional modules from omic and network data. Despite the recognized importance of incorporating domain knowledge to guide biclustering and guarantee a focus on relevant and non-trivial biclusters, this possibility has not yet been comprehensively addressed. This results from the fact that the majority of existing algorithms are only able to deliver sub-optimal solutions with restrictive assumptions on the structure, coherency and quality of biclustering solutions, thus preventing the up-front satisfaction of knowledge-driven constraints...
2016: Algorithms for Molecular Biology: AMB
Yelena Frid, Dan Gusfield
BACKGROUND: The basic RNA secondary structure prediction problem or single sequence folding problem (SSF) was solved 35 years ago by a now well-known [Formula: see text]-time dynamic programming method. Recently three methodologies-Valiant, Four-Russians, and Sparsification-have been applied to speedup RNA secondary structure prediction. The sparsification method exploits two properties of the input: the number of subsequence Z with the endpoints belonging to the optimal folding set and the maximum number base-pairs L...
2016: Algorithms for Molecular Biology: AMB
Roberto Grossi, Costas S Iliopoulos, Robert Mercas, Nadia Pisanti, Solon P Pissis, Ahmad Retha, Fatima Vayani
[This corrects the article DOI: 10.1186/s13015-016-0076-6.].
2016: Algorithms for Molecular Biology: AMB
Timo Beller, Enno Ohlebusch
BACKGROUND: Recently, Marcus et al. (Bioinformatics 30:3476-83, 2014) proposed to use a compressed de Bruijn graph to describe the relationship between the genomes of many individuals/strains of the same or closely related species. They devised an [Formula: see text] time algorithm called splitMEM that constructs this graph directly (i.e., without using the uncompressed de Bruijn graph) based on a suffix tree, where n is the total length of the genomes and g is the length of the longest genome...
2016: Algorithms for Molecular Biology: AMB
Elizabeth T Hobbs, Talmo Pereira, Patrick K O'Neill, Ivan Erill
BACKGROUND: Metagenomics enables the analysis of bacterial population composition and the study of emergent population features, such as shared metabolic pathways. Recently, we have shown that metagenomics datasets can be leveraged to characterize population-wide transcriptional regulatory networks, or meta-regulons, providing insights into how bacterial populations respond collectively to specific triggers. Here we formalize a Bayesian inference framework to analyze the composition of transcriptional regulatory networks in metagenomes by determining the probability of regulation of orthologous gene sequences...
2016: Algorithms for Molecular Biology: AMB
Jianbo Lu, Guoliang Xu, Shihua Zhang, Benzhuo Lu
BACKGROUND: Superpositioning is an important problem in structural biology. Determining an optimal superposition requires a one-to-one correspondence between the atoms of two proteins structures. However, in practice, some atoms are missing from their original structures. Current superposition implementations address the missing data crudely by ignoring such atoms from their structures. RESULTS: In this paper, we propose an effective method for superpositioning pairwise and multiple structures without sequence alignment...
2016: Algorithms for Molecular Biology: AMB
William R Taylor
BACKGROUND: The analysis of correlation in alignments generates a matrix of predicted contacts between positions in the structure and while these can arise for many reasons, the simplest explanation is that the pair of residues are in contact in a three-dimensional structure and are affecting each others selection pressure. To analyse these data, A dynamic programming algorithm was developed for parsing secondary structure interactions in predicted contact maps. RESULTS: The non-local nature of the constraints required an iterated approach (using a "frozen approximation") but with good starting definitions, a single pass was usually sufficient...
2016: Algorithms for Molecular Biology: AMB
Prabina Kumar Meher, Tanmaya Kumar Sahu, A R Rao, S D Wahi
BACKGROUND: Identification of splice sites is essential for annotation of genes. Though existing approaches have achieved an acceptable level of accuracy, still there is a need for further improvement. Besides, most of the approaches are species-specific and hence it is required to develop approaches compatible across species. RESULTS: Each splice site sequence was transformed into a numeric vector of length 49, out of which four were positional, four were dependency and 41 were compositional features...
2016: Algorithms for Molecular Biology: AMB
Benjamin Drinkwater, Michael A Charleston
BACKGROUND: Recent coevolutionary analysis has considered tree topology as a means to reduce the asymptotic complexity associated with inferring the complex coevolutionary interrelationships that arise between phylogenetic trees. Targeted algorithmic design for specific tree topologies has to date been highly successful, with one recent formulation providing a logarithmic space complexity reduction for the dated tree reconciliation problem. METHODS: In this work we build on this prior analysis providing a further asymptotic space reduction, by providing a new formulation for the dynamic programming table used by a number of popular coevolutionary analysis techniques...
2016: Algorithms for Molecular Biology: AMB
Rui Henriques, Sara C Madeira
BACKGROUND: Despite the recognized importance of module discovery in biological networks to enhance our understanding of complex biological systems, existing methods generally suffer from two major drawbacks. First, there is a focus on modules where biological entities are strongly connected, leading to the discovery of trivial/well-known modules and to the inaccurate exclusion of biological entities with subtler yet relevant roles. Second, there is a generalized intolerance towards different forms of noise, including uncertainty associated with less-studied biological entities (in the context of literature-driven networks) and experimental noise (in the context of data-driven networks)...
2016: Algorithms for Molecular Biology: AMB
Krister M Swenson, Pijus Simonaitis, Mathieu Blanchette
BACKGROUND: Traditionally, the merit of a rearrangement scenario between two gene orders has been measured based on a parsimony criteria alone; two scenarios with the same number of rearrangements are considered equally good. In this paper, we acknowledge that each rearrangement has a certain likelihood of occurring based on biological constraints, e.g. physical proximity of the DNA segments implicated or repetitive sequences. RESULTS: We propose optimization problems with the objective of maximizing overall likelihood, by weighting the rearrangements...
2016: Algorithms for Molecular Biology: AMB
Roberto Grossi, Costas S Iliopoulos, Robert Mercas, Nadia Pisanti, Solon P Pissis, Ahmad Retha, Fatima Vayani
BACKGROUND: Sequence comparison is a fundamental step in many important tasks in bioinformatics; from phylogenetic reconstruction to the reconstruction of genomes. Traditional algorithms for measuring approximation in sequence comparison are based on the notions of distance or similarity, and are generally computed through sequence alignment techniques. As circular molecular structure is a common phenomenon in nature, a caveat of the adaptation of alignment techniques for circular sequence comparison is that they are computationally expensive, requiring from super-quadratic to cubic time in the length of the sequences...
2016: Algorithms for Molecular Biology: AMB
Songjian Lu, Gunasheil Mandava, Gaibo Yan, Xinghua Lu
BACKGROUND: The mutual exclusivity of somatic genome alterations (SGAs), such as somatic mutations and copy number alterations, is an important observation of tumors and is widely used to search for cancer signaling pathways or SGAs related to tumor development. However, one problem with current methods that use mutual exclusivity is that they are not signal-based; another problem is that they use heuristic algorithms to handle the NP-hard problems, which cannot guarantee to find the optimal solutions of their models...
2016: Algorithms for Molecular Biology: AMB
Giles Miclotte, Mahdi Heydari, Piet Demeester, Stephane Rombauts, Yves Van de Peer, Pieter Audenaert, Jan Fostier
BACKGROUND: Third generation sequencing platforms produce longer reads with higher error rates than second generation technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes...
2016: Algorithms for Molecular Biology: AMB
Thomas D Wu
BACKGROUND: Suffix arrays and their variants are used widely for representing genomes in search applications. Enhanced suffix arrays (ESAs) provide fast search speed, but require large auxiliary data structures for storing longest common prefix and child interval information. We explore techniques for compressing ESAs to accelerate genomic search and reduce memory requirements. RESULTS: We evaluate various bitpacking techniques that store integers in fewer than 32 bits each, as well as bytecoding methods that reserve a single byte per integer whenever possible...
2016: Algorithms for Molecular Biology: AMB
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