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PubMed2006

Methods for mining HTS data.

Data mining is a fast-growing field that is finding application across a wide range of industries. HTS is a crucial part of the drug discovery process at most large pharmaceutical companies. Accurate analysis of HTS data is, therefore, vital to drug discovery. Given the large quantity of data generated during an HTS, and the importance of analyzing those data effectively, it is unsurprising that data-mining techniques are now increasingly applied to HTS data analysis. Taking a broad view of both the HTS process and the data-mining process, we review recent literature that describes the application of data-mining techniques to HTS data.

Animals↗
PubMed2005

Investigation of protein functions through data-mining on integrated human transcriptome database, H-Invitational database (H-InvDB).

H-Invitational Database (H-InvDB; ) is a human transcriptome database, containing integrative annotation of 41,118 full-length cDNA clones originated from 21,037 loci. H-InvDB is a product of the H-Invitational project, an international collaboration to systematically and functionally validate human genes by analysis of a unique set of high quality full-length cDNA clones using automatic annotation and human curation under unified criteria. Here, 19,574 proteins encoded by these cDNAs were classified into 11,709 function-known and 7865 function-unknown hypothetical proteins by similarity with protein databases and motif prediction (InterProScan). The proportion of "hypothetical proteins" in H-InvDB was as high as 40.4%. In this study, we thus conducted data-mining in H-InvDB with the aim of assigning advanced functional annotations to those hypothetical proteins. First, by data-mining in the H-InvDB version of GTOP, we identified 337 SCOP domains within 7865 H-Inv hypothetical proteins. Second, by data-mining of predicted subcellular localization by SOSUI and TMHMM in H-InvDB, we found 1032 transmembrane proteins within H-Inv hypothetical proteins. These results clearly demonstrate that structural prediction is effective for functional annotation of proteins with unknown functions. All the data in H-InvDB are shown in two main views, the cDNA view and the Locus view, and five auxiliary databases with web-based viewers; DiseaseInfo Viewer, H-ANGEL, Clustering Viewer, G-integra and TOPO Viewer; the data also are provided as flat files and XML files. The data consists of descriptions of their gene structures, novel alternative splicing isoforms, functional RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs in relation with orphan diseases, gene expression profiling, and comparisons with mouse full-length cDNAs in the context of molecular evolution. This unique integrative platform for conducting in silico data-mining represents a substantial contribution to resources required for the exploration of human biology and pathology.

Amino Acid Sequence↗
PubMedDate not supplied

Data mining issues and opportunities for building nursing knowledge.

Health care information systems tend to capture data for nursing tasks, and have little basis in nursing knowledge. Opportunity lies in an important issue where the knowledge used by expert nurses (nursing knowledge workers) in caring for patients is undervalued in the health care system. The complexity of nursing's knowledge base remains poorly articulated and inadequately represented in contemporary information systems. There is opportunity for data mining methods to assist with discovering important linkages between clinical data, nursing interventions, and patient outcomes. Following a brief overview of relevant data mining techniques, a preterm risk prediction case study illustrates the opportunities and describes typical data mining issues in the nontrivial task of building knowledge. Building knowledge in nursing, using data mining or any other method, will make progress only if important data that capture expert nurses' contributions are available in clinical information systems configurations.

Artificial Intelligence↗
PubMed2005

Metal speciation and environmental impact on sandy beaches due to El Salvador copper mine, Chile.

Several coastal rocky shores in northern Chile have been affected by the discharges of copper mine tailings. The present study aims to analyze the chemical speciation of heavy metals in relation to the diversity of sessile species in the rocky intertidal benthic community on the northern Chilean coast, which is influenced by the presence of copper mine tailings. In particular, the chemical forms of Cd, Cu, Fe, Mn, Ni, Pb and Zn in beach sediment samples collected in the area influenced by El Salvador mine tailings were studied using a sequential chemical extraction method. In general, all the elements present a maximum concentration in the area near the actual discharge point (Caleta Palito). With regard to Cu and Mn, the concentrations range between 7.2-985 and 746-22,739 microg/g respectively, being lower than background levels only in the control site of Caleta Zenteno. Moreover, the correlation coefficients highlight that Fe, Mn and Ni correlate significantly and positively in the studied area, showing a possible common, natural origin, whilst Cu shows a negative correlation with Fe, Mn and Ni. It could be possible that Cu has an anthropogenic origin, coming from mining activity in the area. Cd, Fe, Mn, Ni, Pb and Zn are mostly associated with the residual phase, whilst Cu presents a different speciation pattern, as resulted from selective extractions. In fact, Cu is highly associated with organic and exchangeable phases in contaminated localities, whilst it is mainly bound to the residual phase in control sites. Moreover, our results, compared to local biological diversity, showed that those sites characterized by the highest metal concentrations in bioavailable phase had the lowest biodiversity.

Biodiversity↗
PubMed1997

The MinE ring: an FtsZ-independent cell structure required for selection of the correct division site in E. coli.

E. coli cell division is mediated by the FtsZ ring and associated factors. Selection of the correct division site requires the combined action of an inhibitor of FtsZ ring formation (MinCD) and of a topological specificity factor that somehow prevents MinCD action at the middle of the cell (MinE). Here we show that a biologically active MinE-Gfp fusion accumulates in an annular structure near the middle of young cells. Formation of the MinE ring required MinD but was independent of MinC and continued in nondividing cells in which FtsZ function was inhibited. The results indicate that the MinE ring represents a novel cell structure, which allows FtsZ ring formation at midcell by suppressing MinCD activity at this site.

Adenosine Triphosphatases↗
PubMed2003

Application of a data-mining technique to analyze coprescription patterns for antacids in Taiwan.

BACKGROUND: Although antacids are popular drugs with a long history of use, their true utilization patterns-including over-the-counter use-have rarely been documented. Because all antacids are reimbursed under the National Health Insurance program in Taiwan, it is possible to access and analyze nationwide data for these drugs. OBJECTIVES: The purposes of this study were to estimate the scale of antacid prescribing in Taiwan using the national insurance claims for outpatient services and to analyze coprescribing patterns of antacids using modern data-mining techniques. METHODS: The National Health Insurance Research Database in Taiwan supplied the visit-based sampling data sets, which had a sampling ratio of 0.2% for all claims for outpatient medical services in the year 2000. In addition to the plain statistics (ie, data from simple calculations) for antacid prescriptions, we also analyzed relationships between prescriptions for antacids and nonantacid drugs. A data-mining technique-association rule mining-was applied to identify the drugs prescribed in combination with antacids. RESULTS: Among a total of 409,049 eligible prescriptions for 1,704,595 drug items to be administered orally, antacids were present in 213,494 prescriptions (52.2%). Antacid users were generally older than nonusers (mean [SD] age, 39.9 [23.4] years vs 32.4 [25.7] years). In all, 88.8% of antacid items (189,531/213,494) were prescribed without claims diagnoses of gastrointestinal disorders. Using association rule mining with a 1.0% minimum support factor, there were 36 strong association rules between prescriptions for antacids and other drug subgroups at the third level of Anatomical Therapeutic Chemical classification. Nonsteroidal anti-inflammatory drugs and drugs for treating upper respiratory infections played dominant roles in the associations with antacid prescriptions; vitamin B complex and antivertigo preparations were also strongly associated with antacids. CONCLUSIONS: Antacid coprescriptions were common in Taiwan in the year 2000. Further study should investigate whether antacid prescribing patterns are influenced by Taiwanese perceptions that Western drugs injure the stomach.

Adolescent↗
PubMed1997

George Ralph Mines, ventricular fibrillation and the discovery of the vulnerable period.

The discovery of the vulnerable period of the ventricle unmasked one of the major electrical properties of the heart. Since its description by George Ralph Mines in 1914, it has become a crucial concept in understanding the electrophysiologic basis for ventricular fibrillation. Mines also proposed the theoretical basis for the occurrence of reentrant arrhythmias. Although these concepts are widely known, Mines himself remains an obscure figure since his own sudden death at a young age. Mines was a talented researcher who had a short but prolific career in electrophysiology. The historical importance of his work lies in the influence he had on our understanding and treatment of cardiac arrhythmias as well as in the experimental methods he developed, which inspired a new era of quantitative thinking in electrophysiology.

Canada↗
PubMed2006

Mining chemical structural information from the drug literature.

It is easier to find too many documents on a life science topic than to find the right information inside these documents. With the application of text data mining to biological documents, it is no surprise that researchers are starting to look at applications that mine out chemical information. The mining of chemical entities--names and structures--brings with it some unique challenges, which commercial and academic efforts are beginning to address. Ultimately, life science text data mining applications need to focus on the marriage of biological and chemical information.

Chemistry, Pharmaceutical↗
PubMed2002

Getting to the (c)ore of knowledge: mining biomedical literature.

Literature mining is the process of extracting and combining facts from scientific publications. In recent years, many computer programs have been designed to extract various molecular biology findings from Medline abstracts or full-text articles. The present article describes the range of text mining techniques that have been applied to scientific documents. It divides 'automated reading' into four general subtasks: text categorization, named entity tagging, fact extraction, and collection-wide analysis. Literature mining offers powerful methods to support knowledge discovery and the construction of topic maps and ontologies. An overview is given of recent developments in medical language processing. Special attention is given to the domain particularities of molecular biology, and the emerging synergy between literature mining and molecular databases accessible through Internet.

Abstracting and Indexing↗
PubMedDate not supplied

Mortality in land-mine accidents in Iran.

OBJECTIVE: To study the rate of prehospital mortality before establishment of a rescue system for victims of land-mines in Iran. METHOD: Survey at rural clinics in mine-affected areas, and retrospective review of public patient records. RESULTS: A total of 36.4% of casualties from land-mines in the study area died during the period of 1989-1999. The mortality seems highest in those victims who were torso injured. CONCLUSION: The mortality rate from accidents involving land-mines in the study area was high. Most fatalities seemingly occurred in the prehospital setting.

Blast Injuries↗
PubMedDate not supplied

InfVis--platform-independent visual data mining of multidimensional chemical data sets.

The tremendous increase of chemical data sets, both in size and number, and the simultaneous desire to speed up the drug discovery process has resulted in an increasing need for a new generation of computational tools that assist in the extraction of information from data and allow for rapid and in-depth data mining. During recent years, visual data mining has become an important tool within the life sciences and drug discovery area with the potential to help avoiding data analysis from turning into a bottleneck. In this paper, we present InfVis, a platform-independent visual data mining tool for chemists, who usually only have little experience with classical data mining tools, for the visualization, exploration, and analysis of multivariate data sets. InfVis represents multidimensional data sets by using intuitive 3D glyph information visualization techniques. Interactive and dynamic tools such as dynamic query devices allow real-time, interactive data set manipulations and support the user in the identification of relationships and patterns. InfVis has been implemented in Java and Java3D and can be run on a broad range of platforms and operating systems. It can also be embedded as an applet in Web-based interfaces. We will present in this paper examples detailing the analysis of a reaction database that demonstrate how InfVis assists chemists in identifying and extracting hidden information.

Computational Biology↗
PubMed2006

Mineralogy and characterization of arsenic, iron, and lead in a mine waste-derived fertilizer.

The solid-state speciation of arsenic (As), iron (Fe), and lead (Pb) was studied in the mine waste-derived fertilizer Ironite using X-ray absorption spectroscopy, Mössbauer spectroscopy, and aging studies. Arsenic was primarily associated with ferrihydrite (60-70%), with the remainder found in arsenopyrite (30-40%). Lead was observed almost exclusively as anglesite (PbSO4), with <1% observed as galena (PbS). The identification of As in oxidized Fe oxides and Pb as PbSO4 is in disagreement with the dominant reduced phases previously reported and suggests As and Pb contained within the mine waste-derived product are more bioavailable than previously considered. Aging studies in solution result in Ironite granules separating into two distinct fractions, an orange oxide precipitate and a crystalline fraction with a metallic luster. The orange oxide fraction contained As adsorbed/precipitated with ferrihydrite that is released into solution when allowed to equilibrate with water. The fraction with a metallic luster contained pyrite and arsenopyrite. A complete breakdown of arsenopyrite was observed in Ironite aged for 1 month in buffered deionized water. The observations from this study indicate As and Pb exist as oxidized phases that likely develop from the beneficiation and processing of mine tailings for commercial sale. The potential release of As and Pb has important implications for water quality standards and human health. Of particular concern is the quantity of As released from mine waste-derived products due to the new As regulation applied in 2006, limiting As levels to 10 microg L(-1) in drinking water.

Adsorption↗
PubMed2002

Suitability of molecular descriptors for database mining. A comparative analysis.

Database mining methods rely on the molecular descriptors used to characterize a structural database. In the present investigation, five different types of descriptors (log P, UNITY fingerprints, ISIS keys, VolSurf, and GRIND) are applied to characterize various databases (n = 1007, 100, and 229) comprising drugs almost exclusively. The validity of the descriptors is comparatively analyzed via principal component analysis and its hierarchical variant, consensus principal component analysis. Both pharmacodynamic and pharmacokinetic aspects of database mining are treated. For pharmacodynamic aspects, clustering behavior achieved with the different descriptors is tested on the chemically homogeneous beta-blockers, benzodiazepines, and penicillins and on the chemically more diverse class I antiarrhythmics. The following ranking is observed: UNITY fingerprints > ISIS keys and GRIND > VolSurf > log P. Regarding information content, the CPCA superweight plot indicates similarity between fingerprints and ISIS keys as well as between VolSurf and log P, while GRIND differs from all the remaining descriptors. Solubility data and blood/brain barrier penetrating behavior serve as test cases for pharmacokinetic aspects. Comparison of the descriptors applied to these data reveals that VolSurf has the most realistic and consistent behavior, GRIND shows intermediate behavior, while UNITY fingerprints and ISIS keys are not well suited for pharmacokinetic profiling. From this comparative analysis, we conclude that VolSurf descriptors exhibit particular advantages in treating pharmacokinetic aspects; UNITY fingerprints, ISIS keys, and GRIND descriptors are of special value for tackling pharmacodynamic aspects of database mining. The parameter log P is of limited applicability in database mining because of rather poor reliability and lack of completeness of data.

Computing Methodologies↗
PubMed2001

Earthquake triggering by seismic waves following the Landers and Hector Mine earthquakes.

The proximity and similarity of the 1992, magnitude 7.3 Landers and 1999, magnitude 7.1 Hector Mine earthquakes in California permit testing of earthquake triggering hypotheses not previously possible. The Hector Mine earthquake confirmed inferences that transient, oscillatory 'dynamic' deformations radiated as seismic waves can trigger seismicity rate increases, as proposed for the Landers earthquake. Here we quantify the spatial and temporal patterns of the seismicity rate changes. The seismicity rate increase was to the north for the Landers earthquake and primarily to the south for the Hector Mine earthquake. We suggest that rupture directivity results in elevated dynamic deformations north and south of the Landers and Hector Mine faults, respectively, as evident in the asymmetry of the recorded seismic velocity fields. Both dynamic and static stress changes seem important for triggering in the near field with dynamic stress changes dominating at greater distances. Peak seismic velocities recorded for each earthquake suggest the existence of, and place bounds on, dynamic triggering thresholds. These thresholds vary from a few tenths to a few MPa in most places, depend on local conditions, and exceed inferred static thresholds by more than an order of magnitude. At some sites, the onset of triggering was delayed until after the dynamic deformations subsided. Physical mechanisms consistent with all these observations may be similar to those that give rise to liquefaction or cyclic fatigue.

Journal Article↗
PubMed2000

Structural basis for the topological specificity function of MinE.

Correct positioning of the division septum in Escherichia coli depends on the coordinated action of the MinC, MinD and MinE proteins. Topological specificity is conferred on the MinCD division inhibitor by MinE, which counters MinCD activity only in the vicinity of the preferred midcell division site. Here we report the structure of the homodimeric topological specificity domain of Escherichia coli MinE and show that it forms a novel alphabeta sandwich. Structure-directed mutagenesis of conserved surface residues has enabled us to identify a spatially restricted site on the surface of the protein that is critical for the topological specificity function of MinE.

Amino Acid Sequence↗
PubMed2002

Dynamic assembly of MinD into filament bundles modulated by ATP, phospholipids, and MinE.

Accurate positioning of the division septum at the equator of Escherichia coli cells requires a rapid oscillation of MinD ATPase between the polar halves of the cell membrane, together with the division inhibitor MinC, under MinE control. The mechanism underlying MinD oscillation remains poorly understood. Here, we demonstrate that purified MinD assembles into protein filaments in the presence of ATP. Incubation with phospholipid vesicles further stimulates MinD polymerization. Addition of purified MinE in the presence of lipids promotes bundling of MinD filaments as well as their disassembly through activation of MinD ATPase. MinE thus provokes a net decay in the steady-state MinD polymer mass. Taken together, our results suggest that reversible MinD assembly modulated by MinE underlies the dynamic processing of positional information in E. coli to identify precisely the nascent site for cell division.

Adenosine Triphosphatases↗
PubMed2004

Experimental Peptide Identification Repository (EPIR): an integrated peptide-centric platform for validation and mining of tandem mass spectrometry data.

LC MS/MS has become an established technology in proteomic studies, and with the maturation of the technology the bottleneck has shifted from data generation to data validation and mining. To address this bottleneck we developed Experimental Peptide Identification Repository (EPIR), which is an integrated software platform for storage, validation, and mining of LC MS/MS-derived peptide evidence. EPIR is a cumulative data repository where precursor ions are linked to peptide assignments and protein associations returned by a search engine (e.g. Mascot, Sequest, or PepSea). Any number of datasets can be parsed into EPIR and subsequently validated and mined using a set of software modules that overlay the database. These include a peptide validation module, a protein grouping module, a generic module for extracting quantitative data, a comparative module, and additional modules for extracting statistical information. In the present study, the utility of EPIR and associated software tools is demonstrated on LC MS/MS data derived from a set of model proteins and complex protein mixtures derived from MCF-7 breast cancer cells. Emphasis is placed on the key strengths of EPIR, including the ability to validate and mine multiple combined datasets, and presentation of protein-level evidence in concise, nonredundant protein groups that are based on shared peptide evidence.

Breast Neoplasms↗
PubMed1990

Assessment of potential biases in the application of MSHA respirable coal mine dust data to an epidemiologic study.

Systematic errors in exposure data will result in biased estimates of the exposure-response relationship derived from epidemiologic analyses. Thus, adjustment of exposure data to account for identified errors may provide for a more accurate assessment of effect. In preparing to apply respirable coal mine dust exposure data collected by the Mine Safety and Health Administration (MSHA) to a study of the pulmonary status of underground coal miners, an assessment of potential systematic errors was undertaken. Potential errors stemming from adjustment of controls during sampling, concentration-dependent sampling, truncation of sampling results, identified sampling equipment problems, and a disproportionate number of low concentration samples in mine operator-collected samples were identified and evaluated. Methods to account for these errors and adjust mean exposures by mine, occupation, and year are given.

Bias↗