Algorithms for Molecular Biology最新文献

{"title":"Embedding gene trees into phylogenetic networks by conflict resolution algorithms","authors":"Marcin Wawerka, D. Dabkowski, Natalia Rutecka, Agnieszka Mykowiecka, P. Górecki","doi":"10.1186/s13015-022-00218-8","DOIUrl":"https://doi.org/10.1186/s13015-022-00218-8","url":null,"abstract":"","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"76 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78686342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bi-alignments with affine gaps costs","authors":"Peter F. Stadler, S. Will","doi":"10.1186/s13015-022-00219-7","DOIUrl":"https://doi.org/10.1186/s13015-022-00219-7","url":null,"abstract":"","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82802988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adding hydrogen atoms to molecular models via fragment superimposition","authors":"Patrick Kunzmann, Jacob Marcel Anter, K. Hamacher","doi":"10.1186/s13015-022-00215-x","DOIUrl":"https://doi.org/10.1186/s13015-022-00215-x","url":null,"abstract":"","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"17 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65741668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perplexity: evaluating transcript abundance estimation in the absence of ground truth.","authors":"Jason Fan,&nbsp;Skylar Chan,&nbsp;Rob Patro","doi":"10.1186/s13015-022-00214-y","DOIUrl":"https://doi.org/10.1186/s13015-022-00214-y","url":null,"abstract":"<p><strong>Background: </strong>There has been rapid development of probabilistic models and inference methods for transcript abundance estimation from RNA-seq data. These models aim to accurately estimate transcript-level abundances, to account for different biases in the measurement process, and even to assess uncertainty in resulting estimates that can be propagated to subsequent analyses. The assumed accuracy of the estimates inferred by such methods underpin gene expression based analysis routinely carried out in the lab. Although hyperparameter selection is known to affect the distributions of inferred abundances (e.g. producing smooth versus sparse estimates), strategies for performing model selection in experimental data have been addressed informally at best.</p><p><strong>Results: </strong>We derive perplexity for evaluating abundance estimates on fragment sets directly. We adapt perplexity from the analogous metric used to evaluate language and topic models and extend the metric to carefully account for corner cases unique to RNA-seq. In experimental data, estimates with the best perplexity also best correlate with qPCR measurements. In simulated data, perplexity is well behaved and concordant with genome-wide measurements against ground truth and differential expression analysis. Furthermore, we demonstrate theoretically and experimentally that perplexity can be computed for arbitrary transcript abundance estimation models.</p><p><strong>Conclusions: </strong>Alongside the derivation and implementation of perplexity for transcript abundance estimation, our study is the first to make possible model selection for transcript abundance estimation on experimental data in the absence of ground truth.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"6"},"PeriodicalIF":1.0,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8951746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40326298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parsimonious Clone Tree Integration in cancer","authors":"P. Sashittal, Simone Zaccaria, M. El-Kebir","doi":"10.1186/s13015-022-00209-9","DOIUrl":"https://doi.org/10.1186/s13015-022-00209-9","url":null,"abstract":"","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"18 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2022-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86681252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiently sparse listing of classes of optimal cophylogeny reconciliations.","authors":"Yishu Wang,&nbsp;Arnaud Mary,&nbsp;Marie-France Sagot,&nbsp;Blerina Sinaimeri","doi":"10.1186/s13015-022-00206-y","DOIUrl":"https://doi.org/10.1186/s13015-022-00206-y","url":null,"abstract":"<p><strong>Background: </strong>Cophylogeny reconciliation is a powerful method for analyzing host-parasite (or host-symbiont) co-evolution. It models co-evolution as an optimization problem where the set of all optimal solutions may represent different biological scenarios which thus need to be analyzed separately. Despite the significant research done in the area, few approaches have addressed the problem of helping the biologist deal with the often huge space of optimal solutions.</p><p><strong>Results: </strong>In this paper, we propose a new approach to tackle this problem. We introduce three different criteria under which two solutions may be considered biologically equivalent, and then we propose polynomial-delay algorithms that enumerate only one representative per equivalence class (without listing all the solutions).</p><p><strong>Conclusions: </strong>Our results are of both theoretical and practical importance. Indeed, as shown by the experiments, we are able to significantly reduce the space of optimal solutions while still maintaining important biological information about the whole space.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"2"},"PeriodicalIF":1.0,"publicationDate":"2022-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845303/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39788408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new 1.375-approximation algorithm for sorting by transpositions.","authors":"Luiz Augusto G Silva,&nbsp;Luis Antonio B Kowada,&nbsp;Noraí Romeu Rocco,&nbsp;Maria Emília M T Walter","doi":"10.1186/s13015-022-00205-z","DOIUrl":"https://doi.org/10.1186/s13015-022-00205-z","url":null,"abstract":"<p><strong>Background: </strong>SORTING BY TRANSPOSITIONS (SBT) is a classical problem in genome rearrangements. In 2012, SBT was proven to be [Formula: see text]-hard and the best approximation algorithm with a 1.375 ratio was proposed in 2006 by Elias and Hartman (EH algorithm). Their algorithm employs simplification, a technique used to transform an input permutation [Formula: see text] into a simple permutation [Formula: see text], presumably easier to handle with. The permutation [Formula: see text] is obtained by inserting new symbols into [Formula: see text] in a way that the lower bound of the transposition distance of [Formula: see text] is kept on [Formula: see text]. The simplification is guaranteed to keep the lower bound, not the transposition distance. A sequence of operations sorting [Formula: see text] can be mimicked to sort [Formula: see text].</p><p><strong>Results and conclusions: </strong>First, using an algebraic approach, we propose a new upper bound for the transposition distance, which holds for all [Formula: see text]. Next, motivated by a problem identified in the EH algorithm, which causes it, in scenarios involving how the input permutation is simplified, to require one extra transposition above the 1.375-approximation ratio, we propose a new approximation algorithm to solve SBT ensuring the 1.375-approximation ratio for all [Formula: see text]. We implemented our algorithm and EH's. Regarding the implementation of the EH algorithm, two other issues were identified and needed to be fixed. We tested both algorithms against all permutations of size n, [Formula: see text]. The results show that the EH algorithm exceeds the approximation ratio of 1.375 for permutations with a size greater than 7. The percentage of computed distances that are equal to transposition distance, computed by the implemented algorithms are also compared with others available in the literature. Finally, we investigate the performance of both implementations on longer permutations of maximum length 500. From the experiments, we conclude that maximum and the average distances computed by our algorithm are a little better than the ones computed by the EH algorithm and the running times of both algorithms are similar, despite the time complexity of our algorithm being higher.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":" ","pages":"1"},"PeriodicalIF":1.0,"publicationDate":"2022-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8760837/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39913478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An improved approximation algorithm for the reversal and transposition distance considering gene order and intergenic sizes.","authors":"Klairton L Brito,&nbsp;Andre R Oliveira,&nbsp;Alexsandro O Alexandrino,&nbsp;Ulisses Dias,&nbsp;Zanoni Dias","doi":"10.1186/s13015-021-00203-7","DOIUrl":"https://doi.org/10.1186/s13015-021-00203-7","url":null,"abstract":"<p><strong>Background: </strong>In the comparative genomics field, one of the goals is to estimate a sequence of genetic changes capable of transforming a genome into another. Genome rearrangement events are mutations that can alter the genetic content or the arrangement of elements from the genome. Reversal and transposition are two of the most studied genome rearrangement events. A reversal inverts a segment of a genome while a transposition swaps two consecutive segments. Initial studies in the area considered only the order of the genes. Recent works have incorporated other genetic information in the model. In particular, the information regarding the size of intergenic regions, which are structures between each pair of genes and in the extremities of a linear genome.</p><p><strong>Results and conclusions: </strong>In this work, we investigate the SORTING BY INTERGENIC REVERSALS AND TRANSPOSITIONS problem on genomes sharing the same set of genes, considering the cases where the orientation of genes is known and unknown. Besides, we explored a variant of the problem, which generalizes the transposition event. As a result, we present an approximation algorithm that guarantees an approximation factor of 4 for both cases considering the reversal and transposition (classic definition) events, an improvement from the 4.5-approximation previously known for the scenario where the orientation of the genes is unknown. We also present a 3-approximation algorithm by incorporating the generalized transposition event, and we propose a greedy strategy to improve the performance of the algorithms. We performed practical tests adopting simulated data which indicated that the algorithms, in both cases, tend to perform better when compared with the best-known algorithms for the problem. Lastly, we conducted experiments using real genomes to demonstrate the applicability of the algorithms.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"16 1","pages":"24"},"PeriodicalIF":1.0,"publicationDate":"2021-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8717661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39773174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Approximation algorithm for rearrangement distances considering repeated genes and intergenic regions.","authors":"Gabriel Siqueira,&nbsp;Alexsandro Oliveira Alexandrino,&nbsp;Andre Rodrigues Oliveira,&nbsp;Zanoni Dias","doi":"10.1186/s13015-021-00200-w","DOIUrl":"https://doi.org/10.1186/s13015-021-00200-w","url":null,"abstract":"<p><p>The rearrangement distance is a method to compare genomes of different species. Such distance is the number of rearrangement events necessary to transform one genome into another. Two commonly studied events are the transposition, which exchanges two consecutive blocks of the genome, and the reversal, which reverts a block of the genome. When dealing with such problems, seminal works represented genomes as sequences of genes without repetition. More realistic models started to consider gene repetition or the presence of intergenic regions, sequences of nucleotides between genes and in the extremities of the genome. This work explores the transposition and reversal events applied in a genome representation considering both gene repetition and intergenic regions. We define two problems called Minimum Common Intergenic String Partition and Reverse Minimum Common Intergenic String Partition. Using a relation with these two problems, we show a [Formula: see text]-approximation for the Intergenic Transposition Distance, the Intergenic Reversal Distance, and the Intergenic Reversal and Transposition Distance problems, where k is the maximum number of copies of a gene in the genomes. Our practical experiments on simulated genomes show that the use of partitions improves the estimates for the distances.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"16 1","pages":"21"},"PeriodicalIF":1.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8513232/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39539880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heuristic algorithms for best match graph editing.","authors":"David Schaller,&nbsp;Manuela Geiß,&nbsp;Marc Hellmuth,&nbsp;Peter F Stadler","doi":"10.1186/s13015-021-00196-3","DOIUrl":"https://doi.org/10.1186/s13015-021-00196-3","url":null,"abstract":"<p><strong>Background: </strong>Best match graphs (BMGs) are a class of colored digraphs that naturally appear in mathematical phylogenetics as a representation of the pairwise most closely related genes among multiple species. An arc connects a gene x with a gene y from another species (vertex color) Y whenever it is one of the phylogenetically closest relatives of x. BMGs can be approximated with the help of similarity measures between gene sequences, albeit not without errors. Empirical estimates thus will usually violate the theoretical properties of BMGs. The corresponding graph editing problem can be used to guide error correction for best match data. Since the arc set modification problems for BMGs are NP-complete, efficient heuristics are needed if BMGs are to be used for the practical analysis of biological sequence data.</p><p><strong>Results: </strong>Since BMGs have a characterization in terms of consistency of a certain set of rooted triples (binary trees on three vertices) defined on the set of genes, we consider heuristics that operate on triple sets. As an alternative, we show that there is a close connection to a set partitioning problem that leads to a class of top-down recursive algorithms that are similar to Aho's supertree algorithm and give rise to BMG editing algorithms that are consistent in the sense that they leave BMGs invariant. Extensive benchmarking shows that community detection algorithms for the partitioning steps perform best for BMG editing.</p><p><strong>Conclusion: </strong>Noisy BMG data can be corrected with sufficient accuracy and efficiency to make BMGs an attractive alternative to classical phylogenetic methods.</p>","PeriodicalId":50823,"journal":{"name":"Algorithms for Molecular Biology","volume":"16 1","pages":"19"},"PeriodicalIF":1.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39320777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}