The spreadsheet software Microsoft Excel, when used with default settings, is known to convert gene names to dates and floating-point numbers. A programmatic scan of leading genomics journals reveals that approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions.
There is an ever growing number of molecular phylogenetic studies published, due to, in part, the advent of new techniques that allow cheap and quick DNA sequencing. Hence, the demand for relational databases with which to manage and annotate the amassing DNA sequences, genes, voucher specimens and associated biological data is increasing. In addition, a user-friendly interface is necessary for easy integration and management of the data stored in the database back-end. Available databases allow management of a wide variety of biological data. However, most database systems are not specifically constructed with the aim of being an organizational tool for researchers working in phylogenetic inference. We here report a new software facilitating easy management of voucher and sequence data, consisting of a relational database as back-end for a graphic user interface accessed via a web browser. The application, VoSeq, includes tools for creating molecular datasets of DNA or amino acid sequences ready to be used in commonly used phylogenetic software such as RAxML, TNT, MrBayes and PAUP, as well as for creating tables ready for publishing. It also has inbuilt BLAST capabilities against all DNA sequences stored in VoSeq as well as sequences in NCBI GenBank. By using mash-ups and calls to web services, VoSeq allows easy integration with public services such as Yahoo! Maps, Flickr, Encyclopedia of Life (EOL) and GBIF (by generating data-dumps that can be processed with GBIF’s Integrated Publishing Toolkit).
The choice of an efficient document preparation system is an important decision for any academic researcher. To assist the research community, we report a software usability study in which 40 researchers across different disciplines prepared scholarly texts with either Microsoft Word or LaTeX. The probe texts included simple continuous text, text with tables and subheadings, and complex text with several mathematical equations. We show that LaTeX users were slower than Word users, wrote less text in the same amount of time, and produced more typesetting, orthographical, grammatical, and formatting errors. On most measures, expert LaTeX users performed even worse than novice Word users. LaTeX users, however, more often report enjoying using their respective software. We conclude that even experienced LaTeX users may suffer a loss in productivity when LaTeX is used, relative to other document preparation systems. Individuals, institutions, and journals should carefully consider the ramifications of this finding when choosing document preparation strategies, or requiring them of authors.
Teaching bioinformatics at universities is complicated by typical computer classroom settings. As well as running software locally and online, students should gain experience of systems administration. For a future career in biology or bioinformatics, the installation of software is a useful skill. We propose that this may be taught by running the course on GNU/Linux running on inexpensive Raspberry Pi computer hardware, for which students may be granted full administrator access.
Interactive modules for Data Exploration and Visualization (imDEV) is a Microsoft Excel spreadsheet embedded application providing an integrated environment for the analysis of omics data through a user-friendly interface. Individual modules enables interactive and dynamic analyses of large data by interfacing R’s multivariate statistics and highly customizable visualizations with the spreadsheet environment, aiding robust inferences and generating information-rich data visualizations. This tool provides access to multiple comparisons with false discovery correction, hierarchical clustering, principal and independent component analyses, partial least squares regression and discriminant analysis, through an intuitive interface for creating high-quality two- and a three-dimensional visualizations including scatter plot matrices, distribution plots, dendrograms, heat maps, biplots, trellis biplots and correlation networks. Availability and implementation: Freely available for download at http://sourceforge.net/projects/imdev/. Implemented in R and VBA and supported by Microsoft Excel (2003, 2007 and 2010).
Enzyme kinetic parameters are usually determined from initial rates nevertheless, laboratory instruments only measure substrate or product concentration versus reaction time (progress curves). To overcome this problem we present a methodology which uses integrated models based on Michaelis-Menten equation. The most severe practical limitation of progress curve analysis occurs when the enzyme shows a loss of activity under the chosen assay conditions. To avoid this problem it is possible to work with the same experimental points utilized for initial rates determination. This methodology is illustrated by the use of integrated kinetic equations with the well-known reaction catalyzed by alkaline phosphatase enzyme. In this work nonlinear regression was performed with the Solver supplement (Microsoft Office Excel). It is easy to work with and track graphically the convergence of SSE (sum of square errors). The diagnosis of enzyme inhibition was performed according to Akaike information criterion.
Excel2Genie, a simple and user-friendly Microsoft Excel interface, has been developed to the Genie-2000 Spectroscopic Software of Canberra Industries. This Excel application can directly control Canberra Multichannel Analyzer (MCA), process the acquired data and visualize them. Combination of Genie-2000 with Excel2Genie results in remarkably increased flexibility and a possibility to carry out repetitive data acquisitions even with changing parameters and more sophisticated analysis. The developed software package comprises three worksheets: display parameters and results of data acquisition, data analysis and mathematical operations carried out on the measured gamma spectra. At the same time it also allows control of these processes. Excel2Genie is freely available to assist gamma spectrum measurements and data evaluation by the interested Canberra users. With access to the Visual Basic Application (VBA) source code of this application users are enabled to modify the developed interface according to their intentions.
In electrochemical sensing, a number of voltammetric or amperometric curves are obtained which are subsequently processed, typically by evaluating peak currents and peak potentials or wave heights and half-wave potentials, frequently after background correction. Transformations of voltammetric data can help to extract specific information, e.g., the number of transferred electrons, and can reveal aspects of the studied electrochemical system, e.g., the contribution of adsorption phenomena. In this communication, we introduce a LabView-based software package, ‘eL-Chem Viewer’, which is for the analysis of voltammetric and amperometric data, and enables their post-acquisition processing using semiderivative, semiintegral, derivative, integral and elimination procedures. The software supports the single-click transfer of peak/wave current and potential data to spreadsheet software, a feature that greatly improves productivity when constructing calibration curves, trumpet plots and performing similar tasks. eL-Chem Viewer is freeware and can be downloaded from www.lchem.cz/elchemviewer.htm.
Contaminated site remediation is generally difficult, time consuming, and expensive. As a result ranking may aid in efficient allocation of resources. In order to rank the priorities of contaminated sites, input parameters relevant to contaminant fate and transport, and exposure assessment should be as accurate as possible. Yet, in most cases these parameters are vague or not precise. Most of the current remediation priority ranking methodologies overlook the vagueness in parameter values or do not go beyond assigning a contaminated site to a risk class. The main objective of this study is to develop an alternative remedial priority ranking system (RPRS) for contaminated sites in which vagueness in parameter values is considered. RPRS aims to evaluate potential human health risks due to contamination using sufficiently comprehensive and readily available parameters in describing the fate and transport of contaminants in air, soil, and groundwater. Vagueness in parameter values is considered by means of fuzzy set theory. A fuzzy expert system is proposed for the evaluation of contaminated sites and a software (ConSiteRPRS) is developed in Microsoft Office Excel 2007 platform. Rankings are employed for hypothetical and real sites. Results show that RPRS is successful in distinguishing between the higher and lower risk cases.
DIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation (ABC) on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows: (i) the analysis of single nucleotide polymorphism (SNP) data at large number of loci, apart from microsatellite and DNA sequence data; (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics; and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X.