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PubMed2005

Automated derivation and refinement of sequence length patterns for protein sequences using evolutionary computation.

Several stratagems are used in protein bioinformatics for the classification of proteins based on sequence, structure or function. We explore the concept of a minimal signature embedded in a sequence that defines the likely position of a protein in a classification. Specifically, we address the derivation of sparse profiles for the G-protein coupled receptor (GPCR) clan of integral membrane proteins. We present an evolutionary algorithm (EA) for the derivation of sparse profiles (signatures) without the need to supply a multiple alignment. We also apply an evolution strategy (ES) to the problem of pattern and profile refinement. Patterns were derived for the GPCR 'superfamily' and GPCR families 1-3 individually from starting populations of randomly generated signatures, using a database of integral membrane protein sequences and an objective function using a modified receiver operator characteristic (ROC) statistic. The signature derived for the family 1 GPCR sequences was shown to perform very well in a stringent cross-validation test, detecting 76% of unseen GPCR sequences at 5% error. Application of the ES refinement method to a signature developed by a previously described method [Sadowski, M.I., Parish, J.H., 2003. Automated generation and refinement of protein signatures: case study with G-protein coupled receptors. Bioinformatics 19, 727-734] resulted in a 6% increase of coverage for 5% error as measured in the validation test. We note that there might be a limit to this or any classification of proteins based on patterns or schemata.

Algorithms↗

PubMed2004

Nematode.net: a tool for navigating sequences from parasitic and free-living nematodes.

Nematode.net (www.nematode.net) is a web- accessible resource for investigating gene sequences from nematode genomes. The database is an outgrowth of the parasitic nematode EST project at Washington University's Genome Sequencing Center (GSC), St Louis. A sister project at the University of Edinburgh and the Sanger Institute is also underway. More than 295,000 ESTs have been generated from >30 nematodes other than Caenorhabditis elegans including key parasites of humans, animals and plants. Nematode.net currently provides NemaGene EST cluster consensus sequence, enhanced online BLAST search tools, functional classifications of cluster sequences and comprehensive information concerning the ongoing generation of nematode genome data. The long-term goal of nematode.net is to provide the scientific community with the highest quality sequence information and tools for studying these diverse species.

Animals↗

PubMed2004

Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae.

The progress in genome sequencing has led to a rapid accumulation in GenBank submissions of uncharacterized 'hypothetical' genes. These genes, which have not been experimentally characterized and whose functions cannot be deduced from simple sequence comparisons alone, now comprise a significant fraction of the public databases. Expression analyses of Haemophilus influenzae cells using a combination of transcriptomic and proteomic approaches resulted in confident identification of 54 'hypothetical' genes that were expressed in cells under normal growth conditions. In an attempt to understand the functions of these proteins, we used a variety of publicly available analysis tools. Close homologs in other species were detected for each of the 54 'hypothetical' genes. For 16 of them, exact functional assignments could be found in one or more public databases. Additionally, we were able to suggest general functional characterization for 27 more genes (comprising approximately 80% total). Findings from this analysis include the identification of a pyruvate-formate lyase-like operon, likely to be expressed not only in H.influenzae but also in several other bacteria. Further, we also observed three genes that are likely to participate in the transport and/or metabolism of sialic acid, an important component of the H.influenzae lipo-oligosaccharide. Accurate functional annotation of uncharacterized genes calls for an integrative approach, combining expression studies with extensive computational analysis and curation, followed by eventual experimental verification of the computational predictions.

Amino Acid Sequence↗

PubMed2005

Effect of training datasets on support vector machine prediction of protein-protein interactions.

Knowledge of protein-protein interaction is useful for elucidating protein function via the concept of 'guilt-by-association'. A statistical learning method, Support Vector Machine (SVM), has recently been explored for the prediction of protein-protein interactions using artificial shuffled sequences as hypothetical noninteracting proteins and it has shown promising results (Bock, J. R., Gough, D. A., Bioinformatics 2001, 17, 455-460). It remains unclear however, how the prediction accuracy is affected if real protein sequences are used to represent noninteracting proteins. In this work, this effect is assessed by comparison of the results derived from the use of real protein sequences with that derived from the use of shuffled sequences. The real protein sequences of hypothetical noninteracting proteins are generated from an exclusion analysis in combination with subcellular localization information of interacting proteins found in the Database of Interacting Proteins. Prediction accuracy using real protein sequences is 76.9% compared to 94.1% using artificial shuffled sequences. The discrepancy likely arises from the expected higher level of difficulty for separating two sets of real protein sequences than that for separating a set of real protein sequences from a set of artificial sequences. The use of real protein sequences for training a SVM classification system is expected to give better prediction results in practical cases. This is tested by using both SVM systems for predicting putative protein partners of a set of thioredoxin related proteins. The prediction results are consistent with observations, suggesting that real sequence is more practically useful in development of SVM classification system for facilitating protein-protein interaction prediction.

Algorithms↗

PubMed2003

Designing XML schemas for bioinformatics.

Data interchange bioinformatics databases will, in the future, most likely take place using extensible markup language (XML). The document structure will be described by an XML Schema rather than a document type definition (DTD). To ensure flexibility, the XML Schema must incorporate aspects of Object-Oriented Modeling. This impinges on the choice of the data model, which, in turn, is based on the organization of bioinformatics data by biologists. Thus, there is a need for the general bioinformatics community to be aware of the design issues relating to XML Schema. This paper, which is aimed at a general bioinformatics audience, uses examples to describe the differences between a DTD and an XML Schema and indicates how Unified Modeling Language diagrams may be used to incorporate Object-Oriented Modeling in the design of schema.

Biotechnology↗

PubMed2005

Structural characterization of proteins using residue environments.

A primary challenge for structural genomics is the automated functional characterization of protein structures. We have developed a sequence-independent method called S-BLEST (Structure-Based Local Environment Search Tool) for the annotation of previously uncharacterized protein structures. S-BLEST encodes the local environment of an amino acid as a vector of structural property values. It has been applied to all amino acids in a nonredundant database of protein structures to generate a searchable structural resource. Given a query amino acid from an experimentally determined or modeled structure, S-BLEST quickly identifies similar amino acid environments using a K-nearest neighbor search. In addition, the method gives an estimation of the statistical significance of each result. We validated S-BLEST on X-ray crystal structures from the ASTRAL 40 nonredundant dataset. We then applied it to 86 crystallographically determined proteins in the protein data bank (PDB) with unknown function and with no significant sequence neighbors in the PDB. S-BLEST was able to associate 20 proteins with at least one local structural neighbor and identify the amino acid environments that are most similar between those neighbors.

Amino Acids↗

PubMed2000

Application of genomics and proteomics for identification of bacterial gene products as potential vaccine candidates.

The ability of bioinformatics to characterize genomic sequences from pathogenic bacteria for prediction of genes that may encode vaccine candidates, e.g. surface localized proteins, has been evaluated. By applying appropriate tools for genomic mining to the published sequence of Haemophilus influenzae Rd genome, it was possible to identify a putative vaccine candidate, the outer membrane lipoprotein, P6. Proteomics complements genomics by offering abilities to rapidly identify the products of predicted genes, e.g. proteins in outer membrane preparations. The ability to identify the P6 protein uniquely from entries in a sequence database from the expected peptide-mass fingerprint of P6 demonstrates the power of proteomics. The application of proteomics for identification of vaccine candidates for another pathogenic bacterium, Helicobacter pylori using two different approaches is described. The first involves rapid identification of a series of monoclonal antibody reactive proteins from N-terminal sequence tags. The other approach involves identification of proteins in outer membrane preparations by 2-D electrophoresis followed by trypsin digestion and peptide mass map analysis. Our combined studies demonstrate that utilization of genome sequences by application of bioinformatics through genomics and proteomics can expedite the vaccine discovery process by rapidly providing a set of potential candidates for further testing.

Antibodies, Bacterial↗

PubMed2001

Identification of alternate polyadenylation sites and analysis of their tissue distribution using EST data.

Alternate polyadenylation affects a large fraction of higher eucaryote mRNAs, producing mature transcripts with 3' ends of variable length. This variation is poorly represented in the current transcript catalogs derived from whole genome sequences, mostly because such posttranscriptional events are not detectable directly at the DNA level. Alternate polyadenylation of an mRNA is better understood by comparison to EST databases. Comparing ESTs to mRNAs, however, is a difficult task subjected to the pitfalls of internal priming, presence of intron sequences, repeated elements, chimerical ESTs or matches with EST from paralogous genes. We present here a computer program that addresses these problems and displays ESTs matches to a query mRNA sequence to predict alternate polyadenylation and to suggest library-specific forms. The output highlights effective polyadenylation signals, possible sources of artifacts such as A-rich stretches in the mRNA sequences, and allows for a direct visualization of EST libraries using color codes. Statistical biases in the distribution of alternative mRNA forms among EST libraries were systematically sought. About 1450 human and 200 mouse mRNAs displayed such biases, suggesting in each case a tissue- or disease-specific regulation of polyadenylation.

3' Untranslated Regions↗

PubMed2004

In vitro and in silico processes to identify differentially expressed proteins.

We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.

Body Fluids↗

PubMed2003

Hierarchical linear models for the development of growth curves: an example with body mass index in overweight/obese adults.

When data are available on multiple individuals measured at multiple time points that may vary in number or inter-measurement interval, hierarchical linear models (HLM) may be an ideal option. The present paper offers an applied tutorial on the use of HLM for developing growth curves depicting natural changes over time. We illustrate these methods with an example of body mass index (BMI; kg/m(2)) among overweight and obese adults. We modelled among-person variation in BMI growth curves as a function of subjects' baseline characteristics. Specifically, growth curves were modelled with two-level observations, where the first level was each time point of measurement within each individual and the second level was each individual. Four longitudinal databases with measured weight and height met the inclusion criteria and were pooled for analysis: the Framingham Heart Study (FHS); the Multiple Risk Factor Intervention Trial (MRFIT); the National Health and Nutritional Examination Survey I (NHANES-I) and its follow-up study; and the Tecumseh Mortality Follow-up Study (TMFS). Results indicated that significant quadratic patterns of the BMI growth trajectory depend primarily upon a combination of age and baseline BMI. Specifically, BMI tends to increase with time for younger people with relatively moderate obesity (25 BMI <30) but decrease for older people regardless of degree of obesity. The gradients of these changes are inversely related to baseline BMI and do not substantially depend on gender.

Adult↗

PubMed2005

Including mutations from conceptually translated expressed sequence tags into orthologous proteins improves the preliminary assignment of peptide mass fingerprints on non-model genomes.

In order to improve protein assignment from peptide mass fingerprints (PMF) in species with incompletely sequenced genomes, the genus-specific mutations deduced from Expressed sequence tag (EST) sequences were included in the complete reading frames of orthologous proteins, resulting in a new searchable in silico protein database. Using this method in tests on four plant species, the MOWSE score of at least 20% more proteins was improved compared to conventional approaches on crude, total proteins, for middle-sized EST projects. Larger contigs are assembled in more important EST projects and this improves the conventional assignment of the most abundant proteins. However, contigs from minor transcripts remain shorter and the assignment of less abundant proteins, such as those isolated following subcellular fractionment, is improved by searching orthologue-EST conceptual chimeras with the PMF spectra. This strategy may be utilized as a tool to identify potential PMF matches that can be then verified by other experimental approaches (tandem mass spectrometry) to ensure the EST matched chimera identification is accurate.

Amino Acid Sequence↗

PubMed2005

Toxic polypeptides of the hydra--a bioinformatic approach to cnidarian allomones.

Cnidarians such as hydrae and sea anemones are sessile, predatory, soft bodied animals which depend on offensive and defensive allomones for prey capture and survival. These allomones are distributed throughout the entire organism both in specialized stinging cells (nematocytes) and in the body tissues. The cnidarian allomonal system is composed of neurotoxins, cytolysins and toxic phospholipapses. The present bioinformatic survey was motivated by the fact that while hydrae are the most studied model cnidarian, little is known about their allomones. A large-scale EST database from Hydra magnipapillata was searched for orthologs of known cnidarian allomones, as well as for allomones found in other venomous organisms. We show that the hydrae express orthologs of cnidarian phospholipase A2 toxins and cytolysins belonging to the actinoporin family, but could not find orthologs of the 'classic' short chain neurotoxins affecting sodium and potassium conductance. Hydrae also express proteins similar to elapid-like phospholipases, CRISP proteins, Prokineticin-like polypeptides and toxic deoxyribonucleases. Our results illustrate a high level of complexity in the hydra allomonal system, suggest that several toxins represent a basal component of all cnidarian allomones, and raise the intriguing possibility that similar proteins may fulfill both endogenous and allomonal roles in cnidaria.

Amino Acid Sequence↗

PubMed2005

TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies.

In order to understand gene regulation, accurate and comprehensive knowledge of transcriptional regulatory elements is essential. Here, we report our efforts in building a mammalian Transcriptional Regulatory Element Database (TRED) with associated data analysis functions. It collects cis- and trans-regulatory elements and is dedicated to easy data access and analysis for both single-gene-based and genome-scale studies. Distinguishing features of TRED include: (i) relatively complete genome-wide promoter annotation for human, mouse and rat; (ii) availability of gene transcriptional regulation information including transcription factor binding sites and experimental evidence; (iii) data accuracy is ensured by hand curation; (iv) efficient user interface for easy and flexible data retrieval; and (v) implementation of on-the-fly sequence analysis tools. TRED can provide good training datasets for further genome-wide cis-regulatory element prediction and annotation, assist detailed functional studies and facilitate the decipher of gene regulatory networks (http://rulai.cshl.edu/TRED).

Animals↗

PubMed2006

CardioSignal: a database of transcriptional regulation in cardiac development and hypertrophy.

BACKGROUND: Although extensive research has characterized intricate genetic programs in heart system, the information generated is highly fragmented. Here we have developed a new database called CardioSignal, which was designed for integration of regulatory information on the transcriptional regulation involved in heart development and cardiac hypertrophy. METHODS: Data about sequences, positions and functional annotation of transcription binding sites, cis-regulatory modules as well as promoters were collected from scientific literature. Genes involved in both processes were also manually gathered, particularly those preferentially expressed in the heart. Data was stored in MySQL database and Perl was used as the server-side programming language. RESULTS: Currently, CardioSignal contains 677 cardiac genes from twenty species. Among them are 128 cardiac transcription factors. Of the approximately 179 individual promoters from six species, the database also documented 247 experimentally verified binding sites and 64 cis-regulatory modules. CardioSignal may be searched for the promoter of a specific gene by specifying a gene name, Entrez geneID, swissProt accession number and so on. Downstream targets of transcriptional factors and cardiac regulatory modules can also be retrieved through a user-friendly web interface. Also available is experimental supporting evidence. Computational analysis tools were implemented for on-the-fly motif finding and comparative genomic analysis respectively. CONCLUSIONS: CardioSignal offers a unique resource as it contains simultaneously the promoter collected while correlating the information of transcription factor binding sites and cis-regulatory modules from heart system. We are hopeful that its implementation will contribute toward the elucidation of the complex processes in cardiac development and hypertrophy.

Animals↗

PubMed2004

PHYTOPROT: a database of clusters of plant proteins.

All the protein sequences from plants (including Arabidopsis thaliana) available from SwissProt/TrEMBL have been the subject of an all-by-all systematic comparison and grouped into clusters of related proteins. Within each cluster, the sequences have been submitted to pyramidal classification; in the case where two or several subfamilies have been grouped together, the pyramidal tree helps in finding which sequences make the links between subfamilies. In addition, the 'domains' that are common to two or more sequences within a cluster were determined and displayed à la ProDom. The resulting graphical representations proved to be quite efficient in pinpointing those protein sequences suffering from a probable error in the annotation of their genes. The clusters can be searched through various criteria and their pyramidal classifications and their domain representations can be displayed by querying http://genoplante-info. infobiogen.fr/phytoprot. The user can also launch a BLAST search of a query sequence against all the clusters.

Arabidopsis Proteins↗

PubMed2006

[Bioinformatic analysis of adenoma-normal mucosa SSH library of colon].

We established a colonic adenoma-normal mucosa suppressive subtraction hybridization (SSH) library in 1999. In this study, we wanted to explore the expression profile of all candidate genes in this library. We developed an EST pipeline which contained two in-house software packages, nucleic acid analytical software and GetUni. The nucleic acid analytical software, an integrator of the universal bioinformatics tools including phred, phd2fasta, cross_match, repeatmasker and blast2.0, can blast sequences of differential clones with the downloaded non-redundant nucleotide (NR) database. GetUni can cluster these NR sequences into Unigene via matching with the downloaded Homo Sapiens UniGene database. Sixty-two candidate genes in A-N library were obtained via the high throughput automatic gene expression bioinformatics pipeline. Gene Ontology online analysis revealed that ribosome genes and immunity-regulating genes were the two most common categories in the KEGG or Biocarta Pathway. We also detected the expression of 2 genes with highest hits, Reg4 and FAM46A, by semi-quantitative RT-PCR. Both genes were up-regulated in 10 or 9 out of 10 adenomas in comparison with the paired normal mucosa, respectively. The candidate genes in A-N library would be of great significance in disclosing the molecular mechanism underlying in colonic adenoma initiation and progression.

Adenoma↗

PubMedDate not supplied

Proteomics: techniques and applications in cancer research.

Proteomics can be defined as functional analysis of the full set of proteins by high-throughput technologies in a given system. The workflow of proteomics is a multi-step process comprising sample preparation, separation, quantification and identification of proteins. Due to the high complexity of different protein species and the wide dynamic range of protein amount within a cell system it is necessary to apply appropriate analysis methods. One approach is to separate proteins first by two-dimensional gel electrophoresis (2-DE) according to charge and molecular weight. Proteins are then fragmented and analyzed using matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Identification of proteins can be achieved by comparing the mass/charge-ratios of these peptides to respective databases. Proteome analysis with respect to the identification of disease-associated patterns of molecules in different tissues is in the early stages, because standardisation of these techniques often remains to be established. However, proteome analyses is a promising tool to obtain holistic insights into the physiological status of a cell or cellular system. Compared to RNA-based studies some advantages are obvious: (1) post-translational modifications, e. g. phosphorylation, contributing to the activity status can be detected at the protein level only, (2) RNA-levels do not necessarily coincide with protein levels for a particular gene, (3) feedback-mechanisms within regulatory pathways can control protein activity without measurable changes in mRNA content.

Algorithms↗

PubMed2004

An evidence ontology for use in pathway/genome databases.

An important emerging need in Model Organism Databases (MODs) and other bioinformatics databases (DBs) is that of capturing the scientific evidence that supports the information within a DB. This need has become particularly acute as more DB content consists of computationally predicted information, such as predicted gene functions, operons, metabolic pathways, and protein properties. This paper presents an ontology for encoding the type of support and the degree of support for DB assertions, and for encoding the literature source in which that support is reported. The ontology includes a hierarchy of 35 evidence codes for modeling different types of wet-lab and computational evidence for the existence of operons and metabolic pathways, and for gene functions. We also describe an implementation of the ontology within the Pathway Tools software environment, which is used to query and update Pathway/Genome DBs such as EcoCyc, MetaCyc, and HumanCyc.

Computational Biology↗