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At least 613 records · Page 34Linked to original sources
PubMed2003

Pattern identification and classification in gene expression data using an autoassociative neural network model.

The application of DNA microarray technology for analysis of gene expression creates enormous opportunities to accelerate the pace in understanding living systems and identification of target genes and pathways for drug development and therapeutic intervention. Parallel monitoring of the expression profiles of thousands of genes seems particularly promising for a deeper understanding of cancer biology and the identification of molecular signatures supporting the histological classification schemes of neoplastic specimens. However, the increasing volume of data generated by microarray experiments poses the challenge of developing equally efficient methods and analysis procedures to extract, interpret, and upgrade the information content of these databases. Herein, a computational procedure for pattern identification, feature extraction, and classification of gene expression data through the analysis of an autoassociative neural network model is described. The identified patterns and features contain critical information about gene-phenotype relationships observed during changes in cell physiology. They represent a rational and dimensionally reduced base for understanding the basic biology of the onset of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for the identification and classification of pathological states. The proposed method has been tested on two different microarray datasets-Golub's analysis of acute human leukemia [Golub et al. (1999) Science 286:531-537], and the human colon adenocarcinoma study presented by Alon et al. [1999; Proc Natl Acad Sci USA 97:10101-10106]. The analysis of the neural network internal structure allows the identification of specific phenotype markers and the extraction of peculiar associations among genes and physiological states. At the same time, the neural network outputs provide assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

Adenocarcinoma↗
PubMed1995

Influence of the infarct site on the identification of patients with ventricular tachycardia after myocardial infarction based on the time-domain and spectral turbulence analysis of the signal-averaged electrocardiogram.

In a significant proportion of patients with sustained ventricular tachycardia (VT) following anterior myocardial infarction, the areas of slow conduction are activated early during cardiac depolarization. Therefore, they may not be detected by the standard time-domain analysis of the signal-averaged electrocardiogram (SAECG) which is limited to the terminal part of the QRS complex. Spectral turbulence analysis of the SAECG is a new frequency domain technique which examines the whole QRS complex and may improve identification of patients with sustained VT following anterior infarction. We compared the results of time-domain and spectral turbulence analyses of the SAECG in 53 postinfarction patients with sustained VT and in 53 age-, gender- and infarct site-matched patients without VT. The receiver operator characteristic curves have shown that the time-domain analysis resulted in better identification of patients with VT following inferior than following anterior infarction (e.g., at the sensitivity level of 90%, the corresponding values of specificity were 96 and 90%, respectively), whereas the spectral turbulence analysis performed better in the anterior site of infarction. When both time-domain and spectral turbulence analyses were combined, the accuracy of the SAECG for identification of patients with VT following anterior infarction improved, reaching a specificity of 97% at the sensitivity level of 90%. In conclusion (1) spectral turbulence analysis of the SAECG results in better identification of patients with VT following anterior than following inferior infarction, and (2) the combination of time-domain and spectral turbulence analyses of the SAECG may improve identification of patients with VT following anterior infarction.

Aged↗
PubMed2005

Identification, assessment and intervention--Implications of an audit on dyslexia policy and practice in Scotland.

This article reports on research commissioned by the Scottish Executive Education Department (SEED). It aimed to establish the range and extent of policy and provision in the area of specific learning difficulties (SpLD) and dyslexia throughout Scotland. The research was conducted between January and June 2004 by a team from the University of Edinburgh. The information was gathered from a questionnaire sent to all education authorities (100% response rate was achieved). Additional information was also obtained from supplementary interviews and additional materials provided by education authorities. The results indicated that nine education authorities in Scotland (out of 32) have explicit policies on dyslexia and eight authorities have policies on SpLD. It was noted however that most authorities catered for dyslexia and SpLD within a more generic policy framework covering aspects of Special Educational Needs or within documentation on 'effective learning'. In relation to identification thirty-six specific tests, or procedures, were mentioned. Classroom observation, as a procedure was rated high by most authorities. Eleven authorities operated a formal staged process combining identification and intervention. Generally, authorities supported a broader understanding of the role of identification and assessment and the use of standardized tests was only part of a wider assessment process. It was however noted that good practice in identification and intervention was not necessarily dependent on the existence of a dedicated policy on SpLD/dyslexia. Over fifty different intervention strategies/programmes were noted in the responses. Twenty-four authorities indicated that they had developed examples of good practice. The results have implications for teachers and parents as well as those involved in staff development. Pointers are provided for effective practice and the results reflect some of the issues on the current debate on dyslexia particularly relating to early identification.

Aptitude Tests↗
PubMed1998

Optimization of capillary chromatography ion trap-mass spectrometry for identification of gel-separated proteins.

The current paradigm for protein identification using mass spectrometric derived peptide-mass and fragment-ion data employs computer algorithms which match uninterpreted or partially interpreted fragment-ion data to sequence databases, both protein and translated nucleotide sequence databases. Nucleotide sequence databases continue to grow at a rapid rate for some species, providing an unsurpassed resource for protein identification in those species. Ion-trap mass spectrometers with their ability to rapidly generate fragment-ion spectra in a data-dependent manner with high sensitivity and accuracy has led to their increased use for protein identification. We have investigated various parameters on a commercial ion trap-mass spectrometer to enhance our ability to identify peptides separated by capillary reversed phase-high performance liquid chromatography (RP-HPLC) coupled on-line to the mass spectrometer. By systematically evaluating the standard parameters (ion injection time and number of microscans) together with selection of multiple ions from the full mass range, improved tandem mass spectrometry (MS/MS) spectra were generated, facilitating identification of proteins at a low pmol level. Application of this technology to the identification of a standard protein and an unknown from an affinity-enriched mixture are shown.

Amino Acid Sequence↗
PubMed1998

Multiple parameter cross-species protein identification using MultiIdent--a world-wide web accessible tool.

Recent increases in the number of genome sequencing projects means that the amount of protein sequence in databases is increasing at an astonishing pace. In proteome studies, this is facilitating the identification of proteins from molecularly well-defined organisms. However, in studies of proteins from the majority of organisms, proteins must be identified by comparing analytical data to sequences in databases from other species. This process is known as cross-species protein identification. Here we present a new program, MultiIdent, which uses multiple protein parameters such as amino acid composition, peptide masses, sequence tags, estimated protein pI and mass, to achieve cross-species protein identification. The program is structured so that protein amino acid composition, which is highly conserved across species boundaries, first generates a set of candidate proteins. These proteins are then queried with other protein parameters such as sequence tags and peptide masses. A final list of database entries which considers all analytical parameters is presented, ranked by an integrated score. We illustrate the power of the approach with the identification of a set of standard proteins, and the identification of proteins from dog heart separated by two-dimensional gel electrophoresis. The MultiIdent program is available on the world-wide web at: http://www.expasy.ch/sprot/multiident.h tml.

Amino Acid Sequence↗
PubMed2004

Smell identification test as an indicator for cognitive impairment in Alzheimer's disease.

OBJECTIVES: The aim of the present study was to assess olfactory dysfunction in patients with Alzheimer's disease (AD) and to compare utility of the olfactory tests as possible clinical markers. METHODS: Two olfactory identification tests (The Cross-Cultural Smell Identification Test [CC-SIT] and the Picture-based Smell Identification Test [P-SIT]) and the Mini Mental State Examination (MMSE) were administered to patients with AD and age-matched controls. Apolipoprotein E (Apo E) genotypes of patients with AD were identified. RESULTS: Patients with AD had significantly lower olfactory identification scores than age-matched non-demented elderly subjects in both olfactory assessments. In the AD group, the coefficient of correlation between the MMSE scores and the P-SIT scores was higher than that between the MMSE scores and the CC-SIT scores. Receiver operating curve (ROC) analyses for both tests indicated that the P-SIT discriminated AD patients from controls more reliably than did the CC-SIT. Within AD patients, those who were carrying one or two ApoE epsilon4 alleles had a higher coefficient of correlation between the MMSE scores and the P-SIT scores than patients without the ApoE epsilon4 allele. CONCLUSIONS: The results suggest that a short and simple non-lexical olfactory identification test can be useful as a clinical marker of AD appropriate for Japanese elderly population.

Aged↗
PubMed1991

Spine deformity index (SDI) versus other objective procedures of vertebral fracture identification in patients with osteoporosis: a comparative study.

Radiologic identification of vertebral fractures is most important in the diagnosis and monitoring of patients with spinal osteoporosis. Different methods, using vertebral height measurements for fracture identification, have therefore been developed. We compared four methods for fracture identification in spinal x-rays of 62 female patients with primary osteoporosis. The methods of Hedlund and Gallagher, Melton et al., and Davies et al. are based on the ratio of heights within one vertebra or of the height ratios of adjacent vertebrae; all three methods result in counting the number of vertebral fractures. The fourth method of Minne et al. relates anterior, middle and posterior heights of the vertebrae between T5 and L5 to the respective heights of T4. The relative vertebral heights of patients with osteoporosis are compared to the respective relative heights (anterior, middle, and posterior) of normal subjects (T5-L5). This allows the identification of fractured vertebrae, as well as a quantification of the extent of deformation due to these fractures (spine deformity index, SDI). The same measurement data of 62 spinal x-rays of anterior, middle, and posterior heights between T4 and L5 were used to detect vertebral fractures by the four different methods. Correlation between the number of identified fractures by the different methods ranged between r = 0.56 and 0.83. On the other hand, we found a remarkable difference in the mean number of identified fractures and a discrepancy in the identification of single vertebrae as fractured or not. All four methods revealed an accumulation of fractures in the midthoracic area and in the region of transition from thoracic to lumbar spine. Vertebral fractures as identified by SDI were not detected by the other three methods in 12-29% of the cases, even if vertebral height reduction was more than 6 mm. The reliability of each method was examined by the determination of "decreasing" number of fractures during follow-up. A decrease in the number of fractures was found in about 25% patients, if using the three methods that count only the number of fractures. We obtained a 3.6% decrease in the number of fractures using the fourth method. Furthermore, the decrease in SDI values in follow-up was within the range of variance. We therefore believe that SDI and related procedures are reliable in quantifying spinal osteoporosis and monitoring during follow-up.

Adult↗
PubMed2005

CHASE, a charge-assisted sequencing algorithm for automated homology-based protein identifications with matrix-assisted laser desorption/ionization time-of-flight post-source decay fragmentation data.

We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.

Algorithms↗
PubMed2005

In vivo metabolite detection and identification in drug discovery via LC-MS/MS with data-dependent scanning and postacquisition data mining.

An important aspect in drug discovery is the early structural identification of the metabolites of potential new drugs. This gives information on the metabolically labile points in the molecules under investigation, suggesting structural modifications to improve their metabolic stability, and allowing an early safety assessment via the identification of metabolic activation products. From an analytical point of view, metabolite identification still remains a challenging task, especially for in vivo samples, in which they occur at trace levels together with high amounts of endogenous compounds. Here we describe a method, based on LC-ion trap tandem MS, for the rapid in vivo metabolite identification. It is based on the automatic, data-dependent acquisition of multiple product ion MS/MS scans, followed by a postacquisition search, within the entire MS/MS data set obtained, for specific neutral losses or marker ions in the tandem mass spectra of parent molecule and putative metabolites. One advantage of the method is speed, since it requires minimum sample preparation and all the necessary data can be obtained in one chromatographic run. In addition, it is highly sensitive and selective, allowing detection of trace metabolites even in the presence of a complex matrix. As an example of application, we present the studies of the in vivo metabolism of the compound MEN 15916 (1). The method allowed identification of monohydroxy ([M + H](+) = m/z 655), dihydroxy ([M + H](+) = m/z 671), and trihydroxy ([M + H](+) = m/z 687) metabolites, as well as some unexpected biotransformation products such as a carboxylic acid ([M + H](+) = m/z 669), a N-dealkylated metabolite ([M + H](+) = m/z 541), and its hydroxy-analog ([M + H](+) = m/z 557).

Animals↗
PubMed2005

Rapid identification of pathogenic bacteria by capillary electrophoretic analysis of rRNA genes.

Molecular diagnosis is playing an increasingly important role in the rapid detection and identification of pathogenic organisms in clinical samples. The genetic variation of ribosomal genes in bacteria offers an alternative to culturing for the detection and identification of these organisms. Here 16S rRNA and 16S-23S rRNA spacer region genes were chosen as the amplified targets for single-strand conformation polymorphism (SSCP) and restriction fragment length polymorphism (RFLP) capillary electrophoresis analysis and bacterial identification. The multiple fluorescence based SSCP method for the 16S rRNA gene and the RFLP method for the 16S-23S rRNA spacer region gene were developed and applied to the identification of pathogenic bacteria in clinical samples, in which home-made short-chained linear polyacrylamide (LPA) was used as a sieving matrix; a higher sieving capability and shorter analysis time were achieved than with a commercial sieving matrix because of the simplified template preparation procedure. A set of 270 pathogenic bacteria representing 34 species in 14 genera were analyzed, and a total of 34 unique SSCP patterns representing 34 different pathogenic bacterial species were determined. Based on the use of machine code to represent peak patterns developed in this paper, the identification of bacterial species becomes much easier.

Bacteria↗
PubMed2003

Popitam: towards new heuristic strategies to improve protein identification from tandem mass spectrometry data.

In recent years, proteomics research has gained importance due to increasingly powerful techniques in protein purification, mass spectrometry and identification, and due to the development of extensive protein and DNA databases from various organisms. Nevertheless, current identification methods from spectrometric data have difficulties in handling modifications or mutations in the source peptide. Moreover, they have low performance when run on large databases (such as genomic databases), or with low quality data, for example due to bad calibration or low fragmentation of the source peptide. We present a new algorithm dedicated to automated protein identification from tandem mass spectrometry (MS/MS) data by searching a peptide sequence database. Our identification approach shows promising properties for solving the specific difficulties enumerated above. It consists of matching theoretical peptide sequences issued from a database with a structured representation of the source MS/MS spectrum. The representation is similar to the spectrum graphs commonly used by de novo sequencing software. The identification process involves the parsing of the graph in order to emphasize relevant sections for each theoretical sequence, and leads to a list of peptides ranked by a correlation score. The parsing of the graph, which can be a highly combinatorial task, is performed by a bio-inspired algorithm called Ant Colony Optimization algorithm.

Algorithms↗
PubMed2004

Automated methods for improved protein identification by peptide mass fingerprinting.

In order to maximize protein identification by peptide mass fingerprinting noise peaks must be removed from spectra and recalibration is often required. The preprocessing of the spectra before database searching is essential but is time-consuming. Nevertheless, the optimal database search parameters often vary over a batch of samples. For high-throughput protein identification, these factors should be set automatically, with no or little human intervention. In the present work automated batch filtering and recalibration using a statistical filter is described. The filter is combined with multiple data searches that are performed automatically. We show that, using several hundred protein digests, protein identification rates could be more than doubled, compared to standard database searching. Furthermore, automated large-scale in-gel digestion of proteins with endoproteinase LysC, and matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) analysis, followed by subsequent trypsin digestion and MALDI-TOF analysis were performed. Several proteins could be identified only after digestion with one of the enzymes, and some less significant protein identifications were confirmed after digestion with the other enzyme. The results indicate that identification of especially small and low-abundance proteins could be significantly improved after sequential digestions with two enzymes.

Animals↗
PubMed2004

High resolution mass spectrometric alveolar proteomics: identification of surfactant protein SP-A and SP-D modifications in proteinosis and cystic fibrosis patients.

In the present study, one- and two-dimensional gel electrophoresis combined with high resolution Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS) have been applied as powerful approaches for the proteome analysis of surfactant proteins SP-A and SP-D, including identification of structurally modified and truncation forms, in bronchoalveolar lavage fluid from patients with cystic fibrosis, chronic bronchitis and pulmonary alveolar proteinosis. Highly sensitive micropreparation techniques were developed for matrix-assisted laser desorption/ionization (MALDI) FT-ICR MS analysis which provided the identification of surfactant proteins at very low levels. Owing to the high resolution, FT-ICR MS was found to provide substantial advantages for the structural identification of surfactant proteins from complex biological matrices with high mass determination accuracy. Several protein bands corresponding to SP-A and SP-D were identified by MALDI-FT-ICR MS after electrophoretic separation by one- and two-dimensional gel electrophoresis, and provided the identification of structural modifications (hydroxy-proline) and degradation products. The high resolution mass spectrometric proteome analysis should facilitate the unequivocal identification of subunits, aggregations, modifications and degradation products of surfactant proteins and hence contribute to the understanding of the mechanistic basis of lung disease pathogenesis.

Bronchoalveolar Lavage Fluid↗
PubMed2006

Rapid protein identification using direct infusion nanoelectrospray ionization mass spectrometry.

Current protein identification techniques are largely based on MALDI-TOF mass fingerprinting and LC-ESI MS/MS sequence tag analysis. Here we describe an improved method for rapid protein identification that uses direct infusion nanoelectrospray quadrupole time-of-flight (nanoESI QTOF) MS. Protein digests were analyzed without LC separation using nanoESI on a QSTAR XL MS/MS system in information dependent data acquisition mode. The protein identification conditions and parameters were extensively evaluated with in-solution and in-gel digested protein samples. Rapid identification of proteins was achieved and compared directly to the results obtained on the same samples using nanoflow HPLC-MS/MS on the QSTAR system. The increased throughput, reproducibility, the high data quality, and the ease of use make the direct infusion system an efficient and affordable technique for protein identification analysis.

Chromatography, High Pressure Liquid↗
PubMed2004

Method for differential detection and identification of components in protein mixtures analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

We demonstrate that the semi-quantitative information in matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra of tryptically digested protein mixtures can, via a systematic statistical approach, be utilized for the identification of a protein present in different concentrations in two samples. Multiple mass spectra were acquired from a series of tryptically digested test samples in which the concentration of one protein was varied and the concentrations of three other proteins were held constant. The mass spectra were subjected to soft independent modeling of class analogy (SIMCA) analysis assuming that spectra originating from two different samples belonged to different data classes. The SIMCA analysis yielded information on which individual m/z values discriminate between two classes. Protein identification by proteolytic peptide mass fingerprinting was performed with different numbers of mass values in the fingerprint according to the discriminatory information, beginning with the mass corresponding to the best discrimination, followed by the best together with the second best, etc. By using the Probity algorithm, which computes the statistical significance of each identification result, we demonstrate that the first protein identified at a desired significance level (0.001) is the protein that was present in a different concentration in the two samples. Differential analysis of expression is often performed by comparing 2D-gel-spot intensities followed by mass spectrometric identification of the respective protein in each spot that differs. The method presented here has the potential to allow identification of the protein component that differs in cases where a gel-spot is poorly resolved and contains several proteins.

Algorithms↗
PubMed2001

Use of matrix-assisted laser desorption/ionization time-of-flight mass mapping and nanospray liquid chromatography/electrospray ionization tandem mass spectrometry sequence tag analysis for high sensitivity identification of yeast proteins separated by two-dimensional gel electrophoresis.

Current analytical techniques in protein identification by mass spectrometry are based on the generation of peptide mass maps or sequence tags that are idiotypic for the protein sequence. This work reports on the development of the use of mass spectrometric methods for protein identification in research on metabolic pathways of a genetically modified strain of the baker's yeast Saccharomyces cerevisiae. This study describes the use of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass mapping and liquid chromatography/quadrupole time-of-flight electrospray ionization tandem mass spectrometry (LC/Q-TOF-ESI-MS/MS) sequence tag analysis in identification of yeast proteins separated by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). The spots were selected for analysis in order to collect information for future studies, to cover the whole pI range from 3 to 10, and to evaluate information from spots of different intensities. Mass mapping as a rapid, high-throughput method was in most cases sensitive enough for identification. LC/MS/MS was found to be more sensitive and to provide more accurate data, and was very useful when analyzing small amounts of sample. Even one sequence tag acquired by this method could be enough for unambiguous identification, and, in the present case, successfully identified a point mutation.

Amino Acid Sequence↗
PubMed1996

Event-related brain potentials during identification of tachistoscopically presented pictures.

In the present study in 20 healthy subjects, event-related potentials (ERPs) were used to investigate the identification of picture stimuli. Each of 36 landscape pictures and 36 scrambled pictures was presented by a tachistoscope repeatedly until the subject made an identification response. Presentation of one picture was finished after 12 exposures. On the average, landscapes were identified after 5.8 +/- 0.4 exposures; identification responses to scrambles were always wrong and occurred after 11.8 +/- 0.1 exposures. Latencies and amplitude measures were assessed for P2, P3, N400, and the slow wave (SW). Changes in P2 across stimulus presentations did not differ between landscapes and scrambles excluding this component from being indicative for the processing of stimulus meaning. Amplitude of P3 generally declined across presentations, but increased prior to identification for landscape pictures. N400 rapidly declined across presentations of landscapes, but less rapidly for scrambles. The SW increased across stimulus presentations. This increase was more pronounced for landscape than scrambled pictures. The pattern of ERP changes can be interpreted in a framework of a stepwise inhibition of spreading activation within semantic memory with progressing picture identification.

Adult↗
PubMed1995

Odontological identification of the victims of flight AI. IT 5148 air disaster Lyon-Strasbourg 20.01.1992.

The authors report on the contribution of odontological identification of the flight AI. IT 5148 air disaster victims, which occurred on 20th January 1992. The identification procedure was difficult due to large numbers of bodies and mutilations and required the involvement of multidisciplinary teams composed of odontologists, forensic pathologists, radiologists and biologists. The authors set up a simple, discriminant classification which was easy to handle by a multidisciplinary team. Four groups were defined according to the matching characteristics between ante and post mortem data. Perfect matching characteristics between ante and post mortem data were achieved in only 44 cases (Group A). Partial matching characteristics between ante and post mortem data were achieved in 12 cases (Group B). In 29 cases, the insufficiency or absence of odontological data (Group C and D) did not enable the victim to be identified. The results of the investigations showed that the dental examination alone enabled 17 victims to be identified and by including a morphological examination the figure reached 33. By the end of the investigations, 85 of the 87 victims were positively identified. Odontological identification is an essential, accurate and rapid method with allows a body to be identified from its dental characteristics. This anthropometrical method of identification is included with the descriptive and the biological methods. The authors present their experience in performing a formal identification of 44 victims in less than 15 days.

Accidents, Aviation↗