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At least 865 records · Page 48Linked to original sources
PubMed1997

Progress in protein structure prediction.

If protein structure prediction methods are to make any impact on the impending onerous task of analyzing the large numbers of unknown protein sequences generated by the ongoing genome-sequencing projects, it is vital that they make the difficult transition from computational 'gedankenexperiments' to practical software tools. This has already happened in the field of comparative modelling and is currently happening in the threading field. Unfortunately, there is little evidence of this transition happening in the field of ab initio tertiary-structure prediction.

Algorithms↗
PubMed2002

Genome annotation techniques: new approaches and challenges.

As more of the human genome draft sequence is finished, and genomes from other organisms begin to be sequenced, the demand for accurate and reliable genome annotation will increase significantly. To facilitate this industrial-scale genome annotation, automated bioinformatics solutions are increasingly required. As a result, automatic genome annotation systems have become more important in gene discovery within recent years. The design of such large-scale bioinformatics systems is an evolving and dynamic field, based on central cores of bioinformatics software tools and relational databases. Not only must these systems efficiently manage and integrate large volumes of genomic data, but they must also deliver accurate gene predictions and effectively distribute annotation data to the biosciences community.

Computational Biology↗
PubMed1999

Computer-aided target selection-prioritizing targets for antifungal drug discovery.

The entire DNA sequence of the Saccharomyces cerevisiae genome was completed in 1996 and represents the first entirely decoded eukaryotic genome. Because major human pathogenic fungi such as Candida albicans are closely related to S. cerevisiae on a molecular level, the question arises as to how this new information can be used to identify and prioritize those genes that are most suitable as targets for antimycotic drug discovery. To tackle this challenge, a software tool called CATS (computer-aided target selection) was developed. The authors describe how it allows an automated and periodically updated assessment of all S. cerevisiae genes to be carried out with regard to their suitability as antifungal targets.

Journal Article↗
PubMed1999

Molecular diversity and its analysis.

We have recently developed a novel strategy for the rational design of compounds. This 'in silico screening' approach is based on the design and screening of virtual combinatorial libraries. Screening is performed using defined rules derived from a comprehensive description of active and inactive molecules in a relevant learning set. This strategy allows the development of potential ligands without the necessity of any knowledge of the 3D-structure of the target receptor. Key to the success of such methods is the quality of the information being processed, in particular, the diversity of the data in the context of the molecular population in the libraries concerned. Here, we review the problem of data diversity, its definition and its analysis using a new software tool, named Diverser.

Journal Article↗
PubMed2001

Database-assisted promoter analysis.

The analysis of regulatory sequences is greatly facilitated by database-assisted bioinformatic approaches. The TRANSFAC database contains information on transcription factors and their origins, functional properties and sequence-specific binding activities. Software tools enable us to screen the database with a given DNA sequence for interacting transcription factors. If a regulatory function is already attributed to this sequence then the database-assisted identification of binding sites for proteins or protein classes and subsequent experimental verification might establish functionally relevant sites within this sequence. The binding transcription factors and interacting factors might already be present in the database.

Binding Sites↗
PubMed2003

Breeding by design.

Breeding by Design is a concept that aims to control all allelic variation for all genes of agronomic importance. This concept can be achieved through a combination of precise genetic mapping, high-resolution chromosome haplotyping and extensive phenotyping. Thanks to marker technology, software tools and the know-how available today, this goal can now be achieved. Depending on the crop-specific generation time, controlled marker-assisted selection strategies could lead to the production of superior varieties within five to ten years.

Breeding↗
PubMed2003

Step-by-step mark-up of medical guideline documents.

Approaches to formalization of medical guidelines can be divided into model-centric and document-centric. While model-centric approaches dominate in the development of clinical decision support applications, document-centric, mark-up-based formalization is suitable for application tasks requiring the 'literal' content of the document to be transferred into the formal model. Examples of such tasks are logical verification of the document or compliance analysis of health records. The quality and efficiency of document-centric formalization can be improved using a decomposition of the whole process into several explicit steps. We present a methodology and software tool supporting the step-by-step formalization process. The knowledge elements can be marked up in the source text, refined to a tree structure with increasing level of detail, rearranged into an XML knowledge base, and, finally, exported into the operational representation. User-definable transformation rules enable to automate a large part of the process. The approach is being tested in the domain of cardiology. For parts of the WHO/ISH Guidelines for Hypertension, the process has been carried out through all the stages, to the form of executable application, generated automatically from the XML knowledge base.

Artificial Intelligence↗
PubMed2001

The motor nerve simulator.

OBJECTIVE: The aim of the study was to develop a mathematical model of the motor nerve and the action potentials generated from its axons, in order to simulate conditions seen in neurography. The model should be used for the detailed study of the relationship between various nerve characteristics and the electrophysiological recordings obtained. METHODS: The model was developed as a software tool. The signals from individual motor units were real recordings using conventional surface electrodes. There was good agreement between the constructed compound muscle action potential and the one recorded live for the subject from whom the individual signals were obtained. RESULT: A number of physiological characteristics can be changed, including the number of axons, their conduction properties, excitability properties, degree of proximo-distal velocity slowing. F-waves and A-waves can be generated. CONCLUSION: The model gives a good similarity to findings obtained in live recordings. A number of physiological characteristics can be studied individually, something that cannot be done in live recordings. The model can be used in teaching and in research studies of the relationship between nerve properties and neurography parameters.

Action Potentials↗
PubMed2000

Target-based drug discovery for the development of novel antiinfectives.

In the 20th century and especially during the last 50 years, antiinfectives have been increasingly used to control and prevent infectious diseases. Unfortunately the resistance of microorganisms to these pharmaceuticals has increased as well. At the same time the discovery process for novel antiinfectives, the so-called "conventional" screening approach, involves testing natural products or derivatives of known compounds in in vitro cultures. By now it is obvious that this screening approach did not meet the expectations to generate a sufficient number of novel drug candidates. Consequently, studies for selective antiinfectives with new modes of action, which are able to break resistance, are highly desirable for human and animal health. The enormous advance in sequencing technologies--leading to a constantly growing number of known microbial genomes--together with the rapid development of computer power and bioinformatic software tools, now makes it possible to identify genes and gene products that are essential to the pathogenic organisms and are therefore considered to be novel targets for the development of new antiinfectives. When these potential targets have been validated by sophisticated laboratory methods, large diverse compound libraries can be tested in in vitro assays using high-throughput screening. This approach will most likely generate an increasing number of novel lead structures that will be specifically optimized by modern combinatorial chemistry and subsequently lead to new antiinfective candidates strengthening the armoury of weapons available to fight infectious diseases in humans and animals.

Animals↗
PubMed2002

Visualization and evaluation of clusters for exploratory analysis of gene expression data.

Clustering algorithms have been shown to be useful to explore large-scale gene expression profiles. Visualization and objective evaluation of clusters are two important considerations when users are selecting different clustering algorithms, but they are often overlooked. The developments of a framework and software tools that implement comprehensive data visualization and objective measures of cluster quality are crucial. In this paper, we describe a theoretical framework and formalizations for consistently developing clustering algorithms. A new clustering algorithm was developed within the proposed framework. We demonstrate that a theoretically sound principle can be uniformly applied to the developments of cluster-optimization function, comprehensive data-visualization strategy, and objective cluster-evaluation measures as well as actual implementation of the principle. Cluster consistency and quality measures of the algorithm are rigorously evaluated against those of popular clustering algorithms for gene expression data analysis (K-means and self-organizing maps), in four data sets, yielding promising results.

Algorithms↗
PubMed2004

Improving the quality of data in your database: lessons from a cardiovascular center.

BACKGROUND: Creating and having a database should not be an end goal but rather a source of valid data and a means for generating information by which to assess process, performance, and outcome quality. The Cardiovascular Center at Shands Jacksonville (Florida) made measurable improvements in the quality of data in national registries and internally available software tools for collection of patient care data. METHODS: The process of data flow was mapped from source to report submission to identify input timing and process gaps, data sources, and responsible individuals. Cycles of change in data collection and entry were developed and the improvements were tracked. RESULTS: Data accuracy was improved by involving all caregivers in datasheet completion and assisting them with data-field definitions. Using hospital electronic databases decreased the need for manual retrospective review of medical records for datasheet completion. The number of fields with missing values decreased by 83.6%, and the number of missing values decreased from 31.2% to 1.9%. Data accuracy rose dramatically by realtime data entry at point of care. DISCUSSION: Key components to ensuring data quality for process and outcome improvement are (1) education of the caregiver team, (2) process supervision by a database manager, (3) commitment and explicit support from leadership,(4) increased and improved use of electronic data sources, and (5) data entry at point of care.

Cardiology↗
PubMed2001

Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus.

A new method for proteolytic stable isotope labeling is introduced to provide quantitative and concurrent comparisons between individual proteins from two entire proteome pools or their subfractions. Two 18O atoms are incorporated universally into the carboxyl termini of all tryptic peptides during the proteolytic cleavage of all proteins in the first pool. Proteins in the second pool are cleaved analogously with the carboxyl termini of the resulting peptides containing two 16O atoms (i.e., no labeling). The two peptide mixtures are pooled for fractionation and separation, and the masses and isotope ratios of each peptide pair (differing by 4 Da) are measured by high-resolution mass spectrometry. Short sequences and/or accurate mass measurements combined with proteomics software tools allow the peptides to be related to the precursor proteins from which they are derived. Relative signal intensities of paired peptides quantify the expression levels of their precursor proteins from proteome pools to be compared, using an equation described in the paper. Observation of individual (unpaired) peptides is mainly interpreted as differential modification or sequence variation for the protein from the respective proteome pool. The method is evaluated here in a comparison of virion proteins for two serotypes (Ad5 and Ad2) of adenovirus, taking advantage of information already available about protein sequences and concentrations. In general, proteolytic 18O labeling enables a shotgun approach for proteomic studies with quantitation capability and is proposed as a useful tool for comparative proteomic studies of very complex protein mixtures.

Adenoviridae↗
PubMed2005

Curve-fitting method for direct quantitation of compounds in complex biological mixtures using 1H NMR: application in metabonomic toxicology studies.

A new software tool has been developed that provides automated measurement of signal intensities in NMR spectra of complex mixtures without using data reduction procedures. The algorithm finds best-fit transformations between signals in reference compound spectra and the corresponding signals in analyte spectra. Unlike other algorithms, it is insensitive to variation in chemical shift and can even be used for relative quantitation of compounds whose identities have not yet been established. Additionally, the parameters of the transformation provide information and error metrics that may assist in the streamlining of quality control. The approach presented is general in scope but has been tested by application to peak quantitation in NMR spectra of biofluids. Replicate NMR measurements of solutions of biologically important compounds at various concentrations were made. Further NMR data were collected on urine samples from human, rat, and mouse, which were "spiked" with reference compound solutions at known concentrations. Finally, existing data from an independent toxicology project involving several hundred samples were analyzed, and the consistency of the measurements for metabolites that give multiple NMR signals was assessed. The results of all these tests give confidence that the technique can be used in automated quantitation of compounds in large NMR data sets with minimal operator intervention.

Animals↗
PubMedDate not supplied

Pharmacophore identification, in silico screening, and virtual library design for inhibitors of the human factor Xa.

Factor Xa inhibitors are innovative anticoagulant agents that provide a better safety/efficacy profile compared to other anticoagulative drugs. A chemical feature-based modeling approach was applied to identify crucial pharmacophore patterns from 3D crystal structures of inhibitors bound to human factor Xa (Pdb entries 1fjs, 1kns, 1eqz) using the software LIGANDSCOUT and CATALYST. The complex structures were selected regarding the criteria of high inhibitory potency (i.e. all ligands show K(i) values against factor Xa in the subnanomolar range) and good resolution (i.e. at least 2.2 A) in order to generate selective and high quality pharmacophore models. The resulting chemical-feature based hypotheses were used for virtual screening of commercial molecular databases such as the WDI database. Furthermore, a ligand-based molecular modeling approach was performed to obtain common-feature hypotheses that represent the relevant chemical interactions between 10 bioactive factor Xa inhibitors and the protein, respectively. In a next step a virtual combinatorial library was designed in order to generate new compounds with similar chemical and spatial properties as known inhibitors. The software tool ILIB DIVERSE was used for this procedure in order to provide new scaffolds of this group of anticoagulants. Finally we present the combination of these two techniques, hence virtual screening was performed with selective pharmacophore models in a focused virtual combinatorial database. De novo derived molecular scaffolds that were able to adequately satisfy the pharmacophore criteria are revealed and are promising templates for candidates for further development.

Anticoagulants↗
PubMedDate not supplied

Parallel screening: a novel concept in pharmacophore modeling and virtual screening.

Parallel screening comprises a novel in silico method to predict the potential biological activities of a compound by screening it with a multitude of pharmacophore models. Our aim is to provide a fast, large-scale system that allows for virtual activity profiling. In this proof of principle study, carried out with the software tools LigandScout and Catalyst, we present a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all pharmacophore models in order to determine if their biological targets could be correctly predicted via an enrichment of corresponding pharmacophores matching these ligands. The results demonstrate that the desired enrichment, that is, successful virtual activity profiling, was achieved for approximately 90% of all input molecules. We discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the utilized search modus for screening.

Antiviral Agents↗
PubMed2003

On-line analysis of the size distribution of fine and ultrafine aerosol particles in flue and stack gas of a municipal waste incineration plant: effects of dynamic process control measures and emission reduction devices.

The size distribution of particles in the waste gas of a municipal waste incineration plant (23 MW) was measured on-line at two sampling points in the flue-gas duct (700 and 300 degrees C) as well as in the stack gas (80 degrees C). The measurements were performed during both stable combustion conditions and transient operating conditions. The particle measurements were carried out by a mobile system consisting of a home-designed sampling system with dilution device and a scanning mobility particle sizer (SMPS) for the particle size range 17-600 nm as well as an aerodynamic particle sizer (APS) for the size range 500 nm-30 microm. The APS and SMPS data were combined using a special method and a home written software tool. The maximum of the particle-size distribution in the flue gas of the incinerator shifts from about 90 nm at the 700 degrees C sampling point to about 140 nm at the 300 degrees C point, showing the particle growth by coagulation processes and condensation of inorganic and organic gaseous species with decreasing temperature. This finding is consistent with the measured concentration profiles of gaseous organic chemical species in the flue gas. While at flue-gas temperatures of 600-800 degrees C a rich pattern of polycyclic aromatic hydrocarbon species (PAH) is observable, the PAH concentrations are considerably reduced further downstream of the flue-gas channel, where the temperature drops below 500 degrees C. Condensation and reactive bonding of gaseous chemicals onto particulate matter is, among other reasons, responsible for the depletion of gas-phase species. Process control measures, such as firing the backup burners or cleaning of the grate with pressurized air, can cause dynamic changes of the particle-size distribution. Furthermore the flue-gas cleaning measures have great impact onto both the particle concentration and the size distribution. For this reason the impact of one particular emission reduction device, the wet electrostatic dust precipitator (wet-ESP), is evaluated. The wet-ESP reduces considerably the particle concentration over the whole size range. Behind the flue-gas processing units a broad maximum in the particle-size distribution occurs at about 70 nm, but no pronounced particle-size distribution could be observed. The particle concentration level atthis maximum is about 3 magnitudes lower than in the raw flue gas. However, intermittent periods lasting for several minutes of high emissions of ultrafine particles with d < 40 nm were observed. These particles are most likely formed by nucleation processes behind the wet-ESP from gas-phase constituents of the stack gas.

Aerosols↗
PubMedDate not supplied

Automated protein identification by the combination of MALDI MS and MS/MS spectra from different instruments.

The identification of proteins separated on two-dimensional gels is most commonly performed by trypsin digestion and subsequent matrix-assisted laser desorption ionization (MALDI) with time-of-flight (TOF). Recently, atmospheric pressure (AP) MALDI coupled to an ion trap (IT) has emerged as a convenient method to obtain tandem mass spectra (MS/MS) from samples on MALDI target plates. In the present work, we investigated the feasibility of using the two methodologies in line as a standard method for protein identification. In this setup, the high mass accuracy MALDI-TOF spectra are used to calibrate the peptide precursor masses in the lower mass accuracy AP-MALDI-IT MS/MS spectra. Several software tools were developed to automate the analysis process. Two sets of MALDI samples, consisting of 142 and 421 gel spots, respectively, were analyzed in a highly automated manner. In the first set, the protein identification rate increased from 61% for MALDI-TOF only to 85% for MALDI-TOF combined with AP-MALDI-IT. In the second data set the increase in protein identification rate was from 44% to 58%. AP-MALDI-IT MS/MS spectra were in general less effective than the MALDI-TOF spectra for protein identification, but the combination of the two methods clearly enhanced the confidence in protein identification.

Automation↗
PubMed2003

Biomedical informatics for proteomics.

Success in proteomics depends upon careful study design and high-quality biological samples. Advanced information technologies, and also an ability to use existing knowledge to the full, will be crucial in making sense of the data. Despite its genome-scale potential, proteome analysis is at a much earlier stage of development than genomics and gene expression (microarray) studies. Fundamental issues involving biological variability, pre-analytic factors and analytical reproducibility remain to be resolved. Consequently, the analysis of proteomics data is currently informal and relies heavily on expert opinion. Databases and software tools developed for the analysis of molecular sequences and microarrays are helpful, but are limited owing to the unique attributes of proteomics data and differing research goals.

Biomedical Research↗