Review of chemical signature databases

This review assesses the current state of chemical signature databases, the primary characteristics that determine their applicability, characterization of their capability to support spectral identifications, and the target audience to which they are directed. Database file formats, spectrometer operating conditions, and spectral matching tools are found to be primary characteristics that determine the applicability of databases and their ability to support spectral identifications. Chemical signature databases have evolved in two very different directions. One movement offers a single portal for chemical signature determinations by multiple analytical techniques. The other movement is toward highly specialized databases that address narrow scientific disciplines. Both movements are necessary, and serve distinctly different needs in the analytical community.     

Computerized data acquisition and data reduction in spectrophotometric analysis Part 2: numerical analysis with and without an underlying chemical model

Successful numerical analysis of spectrophotometric titrations depends on the availability of high-quality multiwave-length data and on the use of advanced algorithms based on matrix algebra. Two different approaches have been developed: one based on the Law of Mass Action and a specific chemical model and another based exclusively on the original data and making optimum use of the technique of factor analysis.     

Preliminary study of scientific data base,the distributed chemical engineering library

The design principles, system architecture and functions, as well as an application example, of the distributed chemical engineering library (CLIB) are presented. Common characteristics among scientific data bases and common problems in their development, with on-line services, are discussed.     

Multivariate exploratory data analysis in chemical industry

Sizeable data bases are now being routinely generated in a variety of contexts in chemical industry. Statistical investigations of such data bases are aimed both at initially uncovering structure and eventually proposing models, in particular for predicting product quality by the mix or characteristics of the chemical compounds. Online Multivariate Exploratory Graphical Analysis (OMEGA) stands for a structured exploratory study of the relationships in a multivariate data set, where, rather than testing for one specific property, as many clues as possible for interesting structures are searched for by different dimension reductions and succeeding interactive graphical analyses. The stability of the projections obtained by the different dimension reduction methods is assessed by simulation producing graphical displays particularly supporting the identification of influential points. The variation of the predictions obtained by the different dimension reduction methods is assessed by cross-validation delivering misclassification rates or cross-validated R² values. The interpretation of the new coordinates corresponding to dimension reduction is supported by loading simplifications and graphical displays for judging its adequacy. The OMEGA strategy has been found to be an effective tool for routine searching for structure.     

The chemical information system and spectral databases

From 1970 to 1984, the U.S. Government cooperated with various organizations in the support of the development, maintenance, and distribution of a computer-based chemical information system of spectral and other numeric databases, known as the NIH/EPA Chemical Information System (CIS). This presentation discusses the history of the project and related activities in the area of numeric database activities and summarizes the current state of the project.     

A Wireless Sensor Network approach for distributed in-line chemical analysis of water

In this work we propose the implementation of a distributed system based on a Wireless Sensor Network for the control of a chemical analysis system for fresh water. This implementation is presented by describing the nodes that form the distributed system, the communication system by wireless networks, control strategies, and so on.Nitrate, ammonium, and chloride are measured in-line using appropriate ion selective electrodes (ISEs), the results obtained being compared with those provided by the corresponding reference methods. Recovery analyses with ISEs and standard methods, study of interferences, and evaluation of major sensor features have also been carried out.The communication among the nodes that form the distributed system is implemented by means of the utilization of proprietary wireless networks, and secondary data transmission services (GSM or GPRS) provided by a mobile telephone operator. The information is processed, integrated and stored in a control center. These data can be retrieved - through the Internet - so as to know the real-time system status and its evolution.     

Transport phenomena in flow injection analysis without chemical reaction

Dispersion phenomena play a very important role in flow injection analysis. In this paper, physical transport phenomena in flow injection methods are discussed. Three different types of reactor — a straight tube, a helically coiled tube and a new single bead string reactor — are compared. Under similar flow conditions, the dispersion in the single bead string reactor is the lowest. The specific advantages of single bead string reactors are their very simple preparation and maintenance and the good reproducibility of the peaks. It is shown that in open capillary tubes (coiled or not) the Taylor dispersion equation is of very limited use, because the residence times are too short, and because secondary flow occurs in the case of coiled tubes.     

Avoiding spurious correlation in analysis of chemical kinetic data

This communication demonstrates that improperly formulated data analyses can inflate the strength of statistical correlations and result in drawing incorrect conclusions. The widespread misuse of a second-order kinetic model in the recent literature reveals that many chemists are not aware of the dangers of spurious correlation.     

A framework for the evaluation of chemical structure databases

Access to desk-top structure and reaction databases through applications such as Chemical Abstracts' SciFinder, MDL's Beilstein CrossFire, and ISIS Reaction Browser has led to changes in information seeking habits of research chemists, the impact of which has implications when database purchasing decisions are made. A semiquantitative assessment is proposed which takes into account key aspects of structure and reaction databases. Assessment criteria are identified which can be weighted according to an organization's information needs. Values are then assigned to criteria for each data source, after which a formula is applied which leads to an indication of the relative value of systems under consideration. The formula takes into account the cost of database products and also the incremental benefit of adding a new system to an existing collection. This work is presented as a generic approach to the evaluation of databases and is not limited in scope to only structure and reactions databases.     

Scaffold topologies. 2. Analysis of chemical databases

We have systematically enumerated graph representations of scaffold topologies for up to eight-ring molecules and four-valence atoms, thus providing coverage of the lower portion of the chemical space of small molecules (Pollock et al. J. Chem. Inf. Model., this issue). Here, we examine scaffold topology distributions for several databases: ChemNavigator and PubChem for commercially available chemicals, the Dictionary of Natural Products, a set of 2742 launched drugs, WOMBAT, a database of medicinal chemistry compounds, and two subsets of PubChem, "actives" and DSSTox comprising toxic substances. We also examined a virtual database of exhaustively enumerated small organic molecules, GDB (Fink et al. Angew. Chem., Int. Ed. 2005, 44, 1504-1508), and we contrast the scaffold topology distribution from these collections to the complete coverage of up to eight-ring molecules. For reasons related, perhaps, to synthetic accessibility and complexity, scaffolds exhibiting six rings or more are poorly represented. Among all collections examined, PubChem has the greatest scaffold topological diversity, whereas GDB is the most limited. More than 50% of all entries (13 000 000+ actual and 13 000 000+ virtual compounds) exhibit only eight distinct topologies, one of which is the nonscaffold topology that represents all treelike structures. However, most of the topologies are represented by a single or very small number of examples. Within topologies, we found that three-way scaffold connections (3-nodes) are much more frequent compared to four-way (4-node) connections. Fused rings have a slightly higher frequency in biologically oriented databases. Scaffold topologies can be the first step toward an efficient coarse-grained classification scheme of the molecules found in chemical databases.     

A flexible data analysis tool for chemical genetic screens

High-throughput assays generate immense quantities of data that require sophisticated data analysis tools. We have created a freely available software tool, SLIMS (Small Laboratory Information Management System), for chemical genetics which facilitates the collection and analysis of large-scale chemical screening data. Compound structures, physical locations, and raw data can be loaded into SLIMS. Raw data from high-throughput assays are normalized using flexible analysis protocols, and systematic spatial errors are automatically identified and corrected. Various computational analyses are performed on tested compounds, and dilution-series data are processed using standard or user-defined algorithms. Finally, published literature associated with active compounds is automatically retrieved from Medline and processed to yield potential mechanisms of actions. SLIMS provides a framework for analyzing high-throughput assay data both as a laboratory information management system and as a platform for experimental analysis.     

Two-dimensional linear discriminant analysis for classification of three-way chemical data

The two-dimensional linear discriminant analysis (2D-LDA) algorithm was originally proposed in the context of face image processing for the extraction of features with maximal discriminant power. However, despite its promising performance in image processing tasks, the 2D-LDA algorithm has not yet been used in applications involving chemical data. The present paper bridges this gap by investigating the use of 2D-LDA in classification problems involving three-way spectral data. The investigation was concerned with simulated data, as well as real-life data sets involving the classification of dry-cured Parma ham according to ageing by surface autofluorescence spectrometry and the classification of edible vegetable oils according to feedstock using total synchronous fluorescence spectrometry. The results were compared with those obtained by using the spectral data with no feature extraction, U-PLS-DA (Partial Least Squares Discriminant Analysis applied to the unfolded data), and LDA employing TUCKER-3 or PARAFAC scores. In the simulated data set, all methods yielded a correct classification rate of 100%. However, in the Parma ham and vegetable oil data sets, better classification rates were obtained by using 2D-LDA (86% and 100%), compared with no feature extraction (76% and 77%), U-PLS-DA (81% and 92%), PARAFAC-LDA (76% and 86%) and TUCKER3-LDA (86% and 93%).