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PubMed1996

Selection of amino acid parameters for Fourier transform-based analysis of proteins.

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.

Acyl Carrier Protein↗
PubMed2002

Universal sequence map (USM) of arbitrary discrete sequences.

BACKGROUND: For over a decade the idea of representing biological sequences in a continuous coordinate space has maintained its appeal but not been fully realized. The basic idea is that any sequence of symbols may define trajectories in the continuous space conserving all its statistical properties. Ideally, such a representation would allow scale independent sequence analysis--without the context of fixed memory length. A simple example would consist on being able to infer the homology between two sequences solely by comparing the coordinates of any two homologous units. RESULTS: We have successfully identified such an iterative function for bijective mapping psi of discrete sequences into objects of continuous state space that enable scale-independent sequence analysis. The technique, named Universal Sequence Mapping (USM), is applicable to sequences with an arbitrary length and arbitrary number of unique units and generates a representation where map distance estimates sequence similarity. The novel USM procedure is based on earlier work by these and other authors on the properties of Chaos Game Representation (CGR). The latter enables the representation of 4 unit type sequences (like DNA) as an order free Markov chain transition table. The properties of USM are illustrated with test data and can be verified for other data by using the accompanying web-based tool:http://bioinformatics.musc.edu/~jonas/usm/. CONCLUSIONS: USM is shown to enable a statistical mechanics approach to sequence analysis. The scale independent representation frees sequence analysis from the need to assume a memory length in the investigation of syntactic rules.

Algorithms↗
PubMed2006

Expression-guided in silico evaluation of candidate cis regulatory codes for Drosophila muscle founder cells.

While combinatorial models of transcriptional regulation can be inferred for metazoan systems from a priori biological knowledge, validation requires extensive and time-consuming experimental work. Thus, there is a need for computational methods that can evaluate hypothesized cis regulatory codes before the difficult task of experimental verification is undertaken. We have developed a novel computational framework (termed "CodeFinder") that integrates transcription factor binding site and gene expression information to evaluate whether a hypothesized transcriptional regulatory model (TRM; i.e., a set of co-regulating transcription factors) is likely to target a given set of co-expressed genes. Our basic approach is to simultaneously predict cis regulatory modules (CRMs) associated with a given gene set and quantify the enrichment for combinatorial subsets of transcription factor binding site motifs comprising the hypothesized TRM within these predicted CRMs. As a model system, we have examined a TRM experimentally demonstrated to drive the expression of two genes in a sub-population of cells in the developing Drosophila mesoderm, the somatic muscle founder cells. This TRM was previously hypothesized to be a general mode of regulation for genes expressed in this cell population. In contrast, the present analyses suggest that a modified form of this cis regulatory code applies to only a subset of founder cell genes, those whose gene expression responds to specific genetic perturbations in a similar manner to the gene on which the original model was based. We have confirmed this hypothesis by experimentally discovering six (out of 12 tested) new CRMs driving expression in the embryonic mesoderm, four of which drive expression in founder cells.

Amino Acid Motifs↗
PubMed2005

Putting microarrays in a context: integrated analysis of diverse biological data.

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.

Algorithms↗
PubMed1997

Mutational analysis of the C-terminal signal peptide of bovine liver 5'-nucleotidase for GPI anchoring: a study on the significance of the hydrophilic spacer region.

Bovine liver 5'-nucleotidase is a GPI-anchored protein whose Ser523 attaches to GPI as the omega-site. For GPI-modification, pro-protein of the enzyme possesses a signal peptide at the C-terminus, comprising a hydrophilic spacer sequence of 8 amino acid residues and the following hydrophobic region of 17 amino acid residues. The C-terminal signal peptide is replaced by GPI on a luminal leaflet of endoplasmic reticulum. To characterize the C-terminal signal peptide for GPI modification, we constructed a series of deletion and elongation mutant genes, altering length of the hydrophilic spacer sequence by site-directed mutagenesis. Systematic deletion and Ala insertion of the sequence showed that the sequence of 6-14 residues were compatible for GPI modification. For GPI transfer to the pro-protein, the optimum length of spacer sequence would be 8, being consistent with natural selection. The spacer sequence may play a role for leading the omega-residue correctly to the active site of putative GPI transamidase. The elongation of the spacer is more permissible than deletion. Nevertheless, the length of the spacer sequence may influence efficiency of GPI modification by its positive or negative control.

5'-Nucleotidase↗
PubMed2003

Reducing the computational complexity of protein folding via fragment folding and assembly.

Understanding, and ultimately predicting, how a 1-D protein chain reaches its native 3-D fold has been one of the most challenging problems during the last few decades. Data increasingly indicate that protein folding is a hierarchical process. Hence, the question arises as to whether we can use the hierarchical concept to reduce the practically intractable computational times. For such a scheme to work, the first step is to cut the protein sequence into fragments that form local minima on the polypeptide chain. The conformations of such fragments in solution are likely to be similar to those when the fragments are embedded in the native fold, although alternate conformations may be favored during the mutual stabilization in the combinatorial assembly process. Two elements are needed for such cutting: (1) a library of (clustered) fragments derived from known protein structures and (2) an assignment algorithm that selects optimal combinations to "cover" the protein sequence. The next two steps in hierarchical folding schemes, not addressed here, are the combinatorial assembly of the fragments and finally, optimization of the obtained conformations. Here, we address the first step in a hierarchical protein-folding scheme. The input is a target protein sequence and a library of fragments created by clustering building blocks that were generated by cutting all protein structures. The output is a set of cutout fragments. We briefly outline a graph theoretic algorithm that automatically assigns building blocks to the target sequence, and we describe a sample of the results we have obtained.

Algorithms↗
PubMed2005

Kalign--an accurate and fast multiple sequence alignment algorithm.

BACKGROUND: The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families for conserved motifs, phylogeny, structural properties, and to improve sensitivity in homology searching. The availability of complete genome sequences has increased the demands on multiple sequence alignment (MSA) programs. Current MSA methods suffer from being either too inaccurate or too computationally expensive to be applied effectively in large-scale comparative genomics. RESULTS: We developed Kalign, a method employing the Wu-Manber string-matching algorithm, to improve both the accuracy and speed of multiple sequence alignment. We compared the speed and accuracy of Kalign to other popular methods using Balibase, Prefab, and a new large test set. Kalign was as accurate as the best other methods on small alignments, but significantly more accurate when aligning large and distantly related sets of sequences. In our comparisons, Kalign was about 10 times faster than ClustalW and, depending on the alignment size, up to 50 times faster than popular iterative methods. CONCLUSION: Kalign is a fast and robust alignment method. It is especially well suited for the increasingly important task of aligning large numbers of sequences.

Algorithms↗
PubMed2005

Software agents in molecular computational biology.

Progress made in applying agent systems to molecular computational biology is reviewed and strategies by which to exploit agent technology to greater advantage are investigated. Communities of software agents could play an important role in helping genome scientists design reagents for future research. The advent of genome sequencing in cattle and swine increases the complexity of data analysis required to conduct research in livestock genomics. Databases are always expanding and semantic differences among data are common. Agent platforms have been developed to deal with generic issues such as agent communication, life cycle management and advertisement of services (white and yellow pages). This frees computational biologists from the drudgery of having to re-invent the wheel on these common chores, giving them more time to focus on biology and bioinformatics. Agent platforms that comply with the Foundation for Intelligent Physical Agents (FIPA) standards are able to interoperate. In other words, agents developed on different platforms can communicate and cooperate with one another if domain-specific higher-level communication protocol details are agreed upon between different agent developers. Many software agent platforms are peer-to-peer, which means that even if some of the agents and data repositories are temporarily unavailable, a subset of the goals of the system can still be met. Past use of software agents in bioinformatics indicates that an agent approach should prove fruitful. Examination of current problems in bioinformatics indicates that existing agent platforms should be adaptable to novel situations.

Algorithms↗
PubMed1997

Molecular analysis of a compound heterozygote for hypoprothrombinemia and dysprothrombinemia (-G 7248/7249 and ARG 340 TRP).

Hypoprothrombinemia is an uncommon hereditary coagulation defect characterized by low levels of biologically active prothrombin. Automated fluorescence-based DNA sequence analysis of amplified genomic DNA was used to define prothrombin gene regions from a patient with severe functional hypoprothrombinemia and little detectable prothrombin antigen. Two changes that alter amino acid sequence were observed: a deletion of one nucleotide (-G, 7248/7249) in exon 8 of one allele, causing a frameshift at codon 249/250 that results in premature termination of translation; and a C --> T change resulting in the substitution of tryptophan (TGG) for arginine (CGG) at amino acid 340 in exon 10 of the prothrombin gene. Computer modeling of the thrombin molecule confirmed that arginine 340 is located at the surface of the thrombin molecule, which points to the aqueous solvent. As tryptophan is a highly hydrophobic amino acid, the Arg --> Trp change may be associated with instability of the thrombin molecule.

Adult↗
PubMed1999

Differentiation of closely related but biologically distinct cherry isolates of Prunus necrotic ringspot virus by polymerase chain reaction.

Prunus necrotic ringspot ilarvirus (PNRSV) exists as a number of biologically distinct variants which differ in host specificity, serology, and pathology. Previous nucleotide sequence alignment and phylogenetic analysis of cloned reverse transcription-polymerase chain reaction (RT-PCR) products of several biologically distinct sweet cherry isolates revealed correlations between symptom type and the nucleotide and amino acid sequences of the 3a (putative movement protein) and 3b (coat protein) open reading frames. Based upon this analysis, RT-PCR assays have been developed that can identify isolates displaying different symptoms and serotypes. The incorporation of primers in a multiplex PCR protocol permits rapid detection and discrimination among the strains. The results of PCR amplification using type-specific primers that amplify a portion of the coat protein gene demonstrate that the primer-selection procedure developed for PNRSV constitutes a reliable method of viral strain discrimination in cherry for disease control and will also be useful for examining biological diversity within the PNRSV virus group.

DNA Restriction Enzymes↗
PubMed2006

Support vector machine learning from heterogeneous data: an empirical analysis using protein sequence and structure.

MOTIVATION: Drawing inferences from large, heterogeneous sets of biological data requires a theoretical framework that is capable of representing, e.g. DNA and protein sequences, protein structures, microarray expression data, various types of interaction networks, etc. Recently, a class of algorithms known as kernel methods has emerged as a powerful framework for combining diverse types of data. The support vector machine (SVM) algorithm is the most popular kernel method, due to its theoretical underpinnings and strong empirical performance on a wide variety of classification tasks. Furthermore, several recently described extensions allow the SVM to assign relative weights to various datasets, depending upon their utilities in performing a given classification task. RESULTS: In this work, we empirically investigate the performance of the SVM on the task of inferring gene functional annotations from a combination of protein sequence and structure data. Our results suggest that the SVM is quite robust to noise in the input datasets. Consequently, in the presence of only two types of data, an SVM trained from an unweighted combination of datasets performs as well or better than a more sophisticated algorithm that assigns weights to individual data types. Indeed, for this simple case, we can demonstrate empirically that no solution is significantly better than the naive, unweighted average of the two datasets. On the other hand, when multiple noisy datasets are included in the experiment, then the naive approach fares worse than the weighted approach. Our results suggest that for many applications, a naive unweighted sum of kernels may be sufficient. AVAILABILITY: http://noble.gs.washington.edu/proj/seqstruct

Algorithms↗
PubMed2005

Clinical bioinformatics.

Clinical bioinformatics provides biological and medical information to allow for individualized healthcare. In this review, we describe the uses of clinical bioinformatics. After the analysis of the complete human genome sequences, clinical bioinformatics enables researchers to search online biological databases and use the biological information in their medical practices. The data obtained from using microarray is extremely complicated. In clinical bioinformatics, selecting appropriate software to analyze the microarray data for medical decision making is crucial. Proteomics strategy tools usually focus on similarity searches, structure prediction, and protein modeling. In clinical bioinformatics, the proteomic data only have meaning if they are integrated with clinical data. In pharmacogenomics, clinical bioinformatics includes elaborate studies of bioinformatics tools and various facets of proteomics related to drug target identification and clinical validation. Using clinical bioinformatics, researchers apply computational and high-throughput experimental techniques to cancer research and systems biology. Meanwhile, researchers of bioinformatics and medical information have incorporated clinical bioinformatics to improve health care, using biological and medical information. Using the high volume of biological information from clinical bioinformatics will contribute to changes in practice standards in the healthcare system. We believe that clinical bioinformatics provides benefits of improving healthcare, disease prevention and health maintenance as we move toward the era of personalized medicine.

Computational Biology↗
PubMed2005

Microbes on the human vaginal epithelium.

Using solely a gene-based procedure, PCR amplification of the 16S ribosomal RNA gene coupled with very deep sequencing of the amplified products, the microbes on 20 human vaginal epithelia of healthy women have been identified and quantitated. The Lactobacillus content on these 20 healthy vaginal epithelia was highly variable, ranging from 0% to 100%. For four subjects, Lactobacillus was (virtually) the only bacterium detected. However, that Lactobacillus was far from clonal and was a mixture of species and strains. Eight subjects presented complex mixtures of Lactobacillus and other microbes. The remaining eight subjects had no Lactobacillus. Instead, Bifidobacterium, Gardnerella, Prevotella, Pseudomonas, or Streptococcus predominated.

Adult↗
PubMed2000

Automated one-step DNA sequencing based on nanoliter reaction volumes and capillary electrophoresis.

An integrated system with a nano-reactor for cycle-sequencing reaction coupled to on-line purification and capillary gel electrophoresis has been demonstrated. Fifty nanoliters of reagent solution, which includes dye-labeled terminators, polymerase, BSA and template, was aspirated and mixed with the template inside the nano-reactor followed by cycle-sequencing reaction. The reaction products were then purified by a size-exclusion chromatographic column operated at 50 degrees C followed by room temperature on-line injection of the DNA fragments into a capillary for gel electrophoresis. Over 450 bases of DNA can be separated and identified. As little as 25 nl reagent solution can be used for the cycle-sequencing reaction with a slightly shorter read length. Significant savings on reagent cost is achieved because the remaining stock solution can be reused without contamination. The steps of cycle sequencing, on-line purification, injection, DNA separation, capillary regeneration, gel-filling and fluidic manipulation were performed with complete automation. This system can be readily multiplexed for high-throughput DNA sequencing or PCR analysis directly from templates or even biological materials.

Automation↗
PubMed1984

Isolation of a large cholecystokinin precursor from canine brain.

Cholecystokinin (CCK)-like immunoreactivity (CCK-LI) in a pool of 12 dog brains was extracted sequentially into boiling water and cold 2% trifluoroacetic acid. Gel filtration on Sephadex G-50 revealed three main molecular forms detected by a carboxyl-terminal antibody; one was eluted in the position of CCK-58 (58 amino acid residues long); a second, in the position of CCK-8; and a third, near the radioactive iodide marker. When the CCK-LI was purified by affinity chromatography using carboxyl-terminal CCK antibody followed by three steps of reversed-phase high-pressure liquid chromatography, three components were isolated and characterized by sequence microanalysis. The smallest component was the pentapeptide common to gastrin and CCK. The second peak was eluted in the same region as synthetic CCK octapeptide, and sequence analysis showed that the chemical structure of this biologically active region of canine CCK is identical to that found in sheep and pig brains. The 22-residue amino-terminal sequence of brain CCK-58 was: Ala-Val-Gln-Lys-Val-Asp-Gly-Glu-Pro-Arg-Ala-His-Leu-Gly -Ala-Leu-leu-Ala-Arg-Tyr-Ile-Gln-, the same as the sequence found for canine intestinal CCK-58 from this pool of dogs. This is the same sequence others have reported for porcine brain CCK-58 lacking nine amino acid residues (CCK-58 desnonapeptide) except that the porcine peptide had a serine in position 9. The canine CCK amino-terminal sequence differed from the sequence Ala-Gln-Lys-Val-Asn-Ser previously reported for intestinal CCK-58 purified from another pool of dog tissue, but the rest of the residues identified were identical in the two peptides. CCK-58 may be a molecular precursor of the smaller forms of CCK in brain as well as in gut.

Amino Acid Sequence↗
PubMed1991

Growth hormone heterogeneity in American plaice pituitaries: isolation, characterization, and partial amino acid sequence.

Growth hormones (GHs) have been isolated from pituitary glands of American plaice (Hippoglossoides platessoides), a marine flatfish, using affinity and gel filtration chromatography, followed by preparative polyacrylamide gel electrophoresis (PAGE). A bioassay based on serum triiodothyronine elevation in immature rainbow trout was used to monitor biological activity. These GHs originate from two molecular mass regions, 42K and less than 33K relative molecular mass (Mr), in their native state. The 42K Mr region yielded two forms of GH, which differ in terms of quantity and net charge as evidenced by native PAGE, a major variant with a relative mobility of (Rf) 0.22 and a lesser variant with Rf 0.28. The less than 33 Mr region has a single GH species with Rf 0.22. Upon sodium dodecyl sulfate-PAGE, without reduction, both GH variants from the 42K Mr region gave Mrs of 21K, while the GH from the less than 33K Mr region was 20K Mr, typical of monomeric vertebrate GHs. The proteins composing the 42K Mr region are proposed as GH dimers since they yield 21K Mr peptides. The less than 33K Mr region contains a GH monomer (20K Mr) in its native state. An amino-terminal amino acid sequence, identical for both the 42K and the 20K Mr Rf 0.22 forms, has good homology with other complete fish GH sequences near their carboxyl-terminal regions (between amino acids 130 and 196). The GH dimers (42K Mr) predominate in the plaice pituitary, contributing 93% of the total, of which 86% gives rise to the Rf 0.22 variant.

Amino Acid Sequence↗
PubMed2004

A probabilistic measure for alignment-free sequence comparison.

MOTIVATION: Alignment-free sequence comparison methods are still in the early stages of development compared to those of alignment-based sequence analysis. In this paper, we introduce a probabilistic measure of similarity between two biological sequences without alignment. The method is based on the concept of comparing the similarity/dissimilarity between two constructed Markov models. RESULTS: The method was tested against six DNA sequences, which are the thrA, thrB and thrC genes of the threonine operons from Escherichia coli K-12 and from Shigella flexneri; and one random sequence having the same base composition as thrA from E.coli. These results were compared with those obtained from CLUSTAL W algorithm (alignment-based) and the chaos game representation (alignment-free). The method was further tested against a more complex set of 40 DNA sequences and compared with other existing sequence similarity measures (alignment-free). AVAILABILITY: All datasets and computer codes written in MATLAB are available upon request from the first author.

Algorithms↗