Computer applications in the biosciences : CABIOS最新文献

Motivation: Surface-active peptides are amphiphilic in nature and have been shown to have the potential to interact at the membrane interface, possibly by lying parallel to the membrane surface. Present methodology for the identification of these helices uses a fixed window size, is based on a two-dimensional sum of hydrophobicity vectors and gives no measure of the statistical significance for any region identified as amphiphilic. Identification of weakly surface-active structures is difficult and here we have attempted to remedy this by introducing an algorithm which considers three-dimensional geometries and variable window size.

Results: A new measure of membrane-interactive potential is proposed, called the depth-weighted inserted hydrophobicity (DWIH), which is based on the sequestration of hydrophobic residues within a hydrophobic compartment, such as that produced by a membrane bilayer. A statistical significance for this measure has been derived using Monte Carlo techniques. The algorithm is applied to a set of proteins which are thought to anchor to the membrane via C-terminal amphiphilic alpha helices. The DWIH measure appears to allow the identification of this category of membrane-interactive helices which lie near the boundary of the hydrophobic moment plot and which have previously been hard to classify.

Motivation: To enable a new way of submitting sequence information to the EMBL nucleotide database through the WWW. This process of data submission is long and complex, and calls for efficient and user-friendly mechanisms for collection and validation of information.

Results: Described here is a generic, object-oriented data-submission system that is being used for the EMBL database, but can easily, be tailored to serve several data-submission schemes with a relatively short development and implementation time. The program provides the user with a friendly interface that breaks the complex task into smaller, more manageable tasks and, on the other hand, acts as a pre-filter, scanning errors online.

The detection of transcription control elements in DNA sequences became both more important and more complicated by the completion of the first full genome sequencing projects. Rapid evaluation of potential regulatory elements in large amounts of sequence data requires specific methods preferably available as user-friendly computer programs. However, many more algorithms and methods have been published than programs are available, creating problems for scientists who try to select an appropriate method for their needs from the literature. The Internet provides a worldwide and relatively easy access to computer software if the user knows where to look. One of the major problems remaining is how to find the appropriate software. We have compiled a guide detailing where software is available and what is to be expected in terms of interface and data compatibility with other programs. We also show results obtained with each program for several examples. The summarized features of each program should allow scientists to select quickly the method of their choice and inform them where to download the software.

Motivation: A large number of new DNA sequences with virtually unknown functions are generated as the Human Genome Project progresses. Therefore, it is essential to develop computer algorithms that can predict the functionality of DNA segments according to their primary sequences, including algorithms that can predict promoters. Although several promoter-predicting algorithms are available, they have high false-positive detections and the rate of promoter detection needs to be improved further.

Results: In this research, PromFD, a computer program to recognize vertebrate RNA polymerase II promoters, has been developed. Both vertebrate promoters and non-promoter sequences are used in the analysis. The promoters are obtained from the Eukaryotic Promoter Database. Promoters are divided into a training set and a test set. Non-promoter sequences are obtained from the GenBank sequence databank, and are also divided into a training set and a test set. The first step is to search out, among all possible permutations, patterns of strings 5-10 bp long, that are significantly over-represented in the promoter set. The program also searches IMD (Information Matrix Database) matrices that have a significantly higher presence in the promoter set. The results of the searches are stored in the PromFD database, and the program PromFD scores input DNA sequences according to their content of the database entries. PromFD predicts promoters-their locations and the location of potential TATA boxes, if found. The program can detect 71% of promoters in the training set with a false-positive rate of under 1 in every 13,000 bp, and 47% of promoters in the test set with a false-positive rate of under 1 in every 9800 bp. PromFD uses a new approach and its false-positive identification rate is better compared with other available promoter recognition algorithms. The source code for PromFD is in the 'c+2' language.

We have developed a computer program POLYAH and an algorithm for the identification of 3'-processing sites of human mRNA precursors. The algorithm is based on a linear discriminant function (LDF) trained to discriminate real poly(A) signal regions from the other regions of human genes possessing the AATAAA sequence which is most likely non-functional. As the parameters of LDF, various significant contextual characteristics of sequences surrounding AATAAA signals were used. An accuracy of method has been estimated on a set of 131 poly(A) regions and 1466 regions of human genes having the AATAAA sequence. When the threshold was set to predict 86% of poly(A) regions correctly, specificity of 51% and correlation coefficient of 0.62 had been achieved. The precision of this approach is better than for the other methods and has been tested on a larger data set. POLYAH can be used through World Wide Web (at Gene-Finder Home page: URL http:@dot.imgen.bcm.tmc.edu:9331/gene-finder/ gf.html) or by sending files with uncharacterized human sequences to the University of Houston or Weizmann Institute of Science e-mail servers.

Motivation: Quick and easy gene mapping by the use of a panel of cytogenetically characterized somatic cell hybrids is possible, even if some discordant experimental results arise.

Results: An interactive program is proposed and is made available on a WWW site to users of a somatic cell hybrid panel. Assignments to chromosomes and subchromosomal regions are based on likelihood calculations and Bayes' theorem, and a confidence level is provided. The method is illustrated in the case of the pig genome.

This paper presents an algorithm for constructing an optimal alignment between a three-dimensional protein structure template and an amino acid sequence. A protein structure template is given as a sequence of amino acid residue positions in three-dimensional space, along with an array of physical properties attached to each position; these residue positions are sequentially grouped into a series of core secondary structures (central helices and beta sheets). In addition to match scores and gap penalties, as in a traditional sequence-sequence alignment problem, the quality of a structure-sequence alignment is also determined by interaction preferences among amino acids aligned with structure positions that are spatially close (we call these 'long-range interactions'). Although it is known that constructing such a structure-sequence alignment in the most general form is NP-hard, our algorithm runs in polynomial time when restricted to structures with a 'modest' number of long-range amino acid interactions. In the current work, long-range interactions are limited to interactions between amino acids from different core secondary structures. Dividing the series of core secondary structures into two subseries creates a cut set of long-range interactions. If we use N, M and C to represent the size of an amino acid sequence, the size of a structure template, and the maximum cut size of long-range interactions, respectively, the algorithm finds an optimal structure-sequence alignment in O(21C NM) time, a polynomial function of N and M when C = O(log(N + M)). When running on structure-sequence alignment problems without long-range intersections, i.e. C = 0, the algorithm achieves the same asymptotic computational complexity of the Smith-Waterman sequence-sequence alignment algorithm.

Three different implementations of the 3-pass algorithm of image and volume data rotation are illustrated and discussed. The three protocols use interpolation in real domain, with a peculiar implementation of the Shannon reconstruction, or phase shifts in Fourier domain. Accuracy and speed of the three methods are compared with corresponding values obtained with a 1-pass method. The results indicate that for low or moderate accuracy, 1-pass is more convenient than 3-pass rotation for both accuracy and speed. Very accurate rotations can be obtained in reasonable time if all steps of 3-pass rotation are performed in the Fourier domain.

LALNVIEW is a graphical program for visualising local alignments between two sequences (protein or nucleic acids). Sequences are represented by coloured rectangles to give an overall picture of their similarities. LALNVIEW can display sequence features (exon, intron, active site, domain, propeptide, etc.) along with the alignment. When using LALNVIEW through our Web servers, sequence features are automatically extracted from database annotations (SWISS-PROT, GenBank, EMBL or HOVERGEN) and displayed with the alignment. LALNVIEW is a useful tool for analysing pairwise sequence alignments and for making the link between sequence homology and what is known about the structure or function of sequences. LALNVIEW executables for UNIX, Macintosh and PC computers are freely available from our server (http:// expasy.hcuge.ch/sprot/lalnview.html).

Fourier analysis of the parametric profile of a sequence for the detection and localization of the structural motifs that are characteristic for biologically related proteins has been proposed. In order to select parameters that are most appropriate for this analysis, the informational capacity of 226 physicochemical, thermodynamic, structural and statistical amino acid parameters was analyzed. Based on the results, obtained for the four functionally unrelated protein model groups (lysozyme c, HIV-1 gp120, tubulin and tau proteins, and steroid hormone receptors), the electron-ion interaction potential has been selected as the unique amino acid property that can be used in Fourier transform-based analysis of proteins, independently of their biological function.