776 research outputs found
Evolutionary Inference via the Poisson Indel Process
We address the problem of the joint statistical inference of phylogenetic
trees and multiple sequence alignments from unaligned molecular sequences. This
problem is generally formulated in terms of string-valued evolutionary
processes along the branches of a phylogenetic tree. The classical evolutionary
process, the TKF91 model, is a continuous-time Markov chain model comprised of
insertion, deletion and substitution events. Unfortunately this model gives
rise to an intractable computational problem---the computation of the marginal
likelihood under the TKF91 model is exponential in the number of taxa. In this
work, we present a new stochastic process, the Poisson Indel Process (PIP), in
which the complexity of this computation is reduced to linear. The new model is
closely related to the TKF91 model, differing only in its treatment of
insertions, but the new model has a global characterization as a Poisson
process on the phylogeny. Standard results for Poisson processes allow key
computations to be decoupled, which yields the favorable computational profile
of inference under the PIP model. We present illustrative experiments in which
Bayesian inference under the PIP model is compared to separate inference of
phylogenies and alignments.Comment: 33 pages, 6 figure
DIALIGN-TX and multiple protein alignment using secondary structure information at GOBICS
We introduce web interfaces for two recent extensions of the multiple-alignment program DIALIGN. DIALIGN-TX combines the greedy heuristic previously used in DIALIGN with a more traditional ‘progressive’ approach for improved performance on locally and globally related sequence sets. In addition, we offer a version of DIALIGN that uses predicted protein secondary structures together with primary sequence information to construct multiple protein alignments. Both programs are available through ‘Göttingen Bioinformatics Compute Server’ (GOBICS)
Bioinformatic tools and guideline for PCR primer design
Bioinformatics has become an essential tool not only for basic research but also for applied research in biotechnology and biomedical sciences. Optimal primer sequence and appropriate primer concentration are essential for maximal specificity and efficiency of PCR. A poorly designed primer can result in little or no product due to non-specific amplification and/or primer-dimer formation, which can become competitive enough to suppress product formation. There are several online tools devoted to serving molecular biologist design effective PCR primers. This review intends to provide a guide to choosing the most efficient way to design a new specific-primer by applying current publicly available links and Web services. Also, the purpose here is to provide general recommendations for the design and use of PCR primers.
(African Journal of Biotechnology: 2003 2(5): 91-95
ReformAlign: improved multiple sequence alignments using a profile-based meta-alignment approach
Background: Obtaining an accurate sequence alignment is fundamental for consistently analyzing biological data. Although this problem may be efficiently solved when only two sequences are considered, the exact inference of the optimal alignment easily gets computationally intractable for the multiple sequence alignment case. To cope with the high computational expenses, approximate heuristic methods have been proposed that address the problem indirectly by progressively aligning the sequences in pairs according to their relatedness. These methods however are not flexible to change the alignment of an already aligned group of sequences in the view of new data, resulting thus in compromises on the quality of the deriving alignment. In this paper we present ReformAlign, a novel meta-alignment approach that may significantly improve on the quality of the deriving alignments from popular aligners. We call ReformAlign a meta-aligner as it requires an initial alignment, for which a variety of alignment programs can be used. The main idea behind ReformAlign is quite straightforward: at first, an existing alignment is used to construct a standard profile which summarizes the initial alignment and then all sequences are individually re-aligned against the formed profile. From each sequence-profile comparison, the alignment of each sequence against the profile is recorded and the final alignment is indirectly inferred by merging all the individual sub-alignments into a unified set. The employment of ReformAlign may often result in alignments which are significantly more accurate than the starting alignments. Results: We evaluated the effect of ReformAlign on the generated alignments from ten leading alignment methods using real data of variable size and sequence identity. The experimental results suggest that the proposed meta-aligner approach may often lead to statistically significant more accurate alignments. Furthermore, we show that ReformAlign results in more substantial improvement in cases where the starting alignment is of relatively inferior quality or when the input sequences are harder to align. Conclusions: The proposed profile-based meta-alignment approach seems to be a promising and computationally efficient method that can be combined with practically all popular alignment methods and may lead to significant improvements in the generated alignments
Mirage: A Novel Multiple Protein Sequence Alignment Tool
A fundamental problem in computational biology is the organization of many related sequences into a multiple sequence alignment (MSA) [2]. MSAs have a range of research applications, such as inferring phylogeny [22] and identifying regions of conserved sequence that indicate functional similarity [18]. In the case of protein isoforms, MSAs are valuable tools for transitively annotating post-translational modifications (PTMs) by enabling information transfer between known PTM sites and the sites that they align to [11].
For protein MSA tools, one challenging biological phenomenon is alternative splicing, wherein identical genomic sequence will differentially select from a subset of available coding regions (exons), depending on the biochemical environment [21]. Traditional methods struggle to align the islands of non-homologous sequence produced by alternative splicing, and frequently compensate for the penalties incurred from aligning non-identical characters by aligning small pieces of relatively similar sequence from alternative exons in a way that avoids extreme gap penalties but falsely indicates sequence homology.
Presented here is Mirage, a novel protein MSA tool capable of accurately aligning alternatively spliced proteins by first mapping proteins to the genomic sequence that encoded them and then aligning proteins to one another based on the relative positions of their coding DNA. This method of transitive alignment demonstrates an awareness of intron splice site locations and resolves the problems associated with alternative splicing in traditional MSA tools
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