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PubMed1989

Exposure to shock and vibration and symptoms in workers using impact power tools.

In The Netherlands damage to health due to occupational exposure to shock and vibration is seldom reported. A survey was therefore made of the nature, extent and severity of exposure to shock and vibration. This paper presents the results of an epidemiological study, by questionnaire, among workers using impact power tools. Data were collected about exposure time, symptoms and the subjective workload. A prevalence rate of 17% for symptoms of white finger was found. In the logistic regression symptoms of back pain showed an increased prevalence with increasing total time exposed to vibration. This study shows that exposure to vibration due to working with impact power tools, either alone or in combination with ergonomically bad working conditions, probably contributes to these symptoms. An estimate of the population at risk showed that over 30,000 workers in The Netherlands who use impact power tools are exposed to a vibration intensity of 10-40 m s-2. This intensity exceeds the standards advocated in draft standards in the U.K. (BSI, 1987) and U.S.A. (ACGIH, 1984). The results also provide evidence that in The Netherlands exposure to hand-arm vibration damages health. It is suggested that damage to health due to occupational exposure to vibration is underestimated by the Dutch occupational health services. It was concluded that more investigation is needed to evaluate the precise nature of occupational exposure to vibration in order to provide a basis for its reduction or elimination.

Finger Injuries↗

PubMed2002

A modern tool for classical plant growth analysis.

We present an all-inclusive software tool for dealing with the essential core of mathematical and statistical calculations in plant growth analysis. The tool calculates up to six of the most fundamental growth parameters according to a purely 'classical' approach across one harvest-interval. All of the estimates carry standard errors and 95 % confidence limits. The tool is written in Microsoft Excel 2000 and is available free of charge for use in teaching and research from www.aob.oupjournals.org article supplementary data.

Algorithms↗

PubMed2003

Transposable elements as tools for genomics and genetics in Drosophila.

The P-element has been the workhorse of Drosophila genetics since it was developed as a tool for transgenesis in 1982; the subsequent development of a variety of systems based on the transposon have provided a range of powerful and flexible tools for genetics and genomics applications. P-element insertions are frequently used as starting-points for generating chromosomal deletions to remove flanking genes, either by screening for imprecise excision events or by selecting for male recombination events. Elements that utilise the yeast FLP/FLP recombination target (FRT) site-specific recombination system have been widely used to generate molecularly marked mitotic clones for mosaic analysis, extending the reach of this powerful genetic tool to virtually all areas of developmental biology. P-elements are still widely used as traditional mutagenesis reagents and form the backbone of projects aimed at generating insertions in every predicted gene in the fly genome. In addition, vectors based on the FLP/FRT system are being used for genome-wide applications, including the development of molecularly-mapped deletion and duplication kits. In addition to these 'traditional' genetic approaches, a variety of engineered elements have been developed for a wide range of transgenic applications, including enhancer trapping, gene-tagging, targeted misexpression, RNA interference (RNAi) delivery and homologous recombination/gene replacement. To complement the use of P-elements, alternative transposon vectors have been developed. The most widely used of these are the lepidopteran element piggyBac and a Drosophila hydei transposon, Minos. In total, a range of transposon vectors offers the Drosophila biologist considerable flexibility and sophistication in manipulating the genome of the fly and has allowed rapid advances in all areas of developmental biology and genome science.

Animals↗

PubMed2003

Peptide aptamers: tools for biology and drug discovery.

Peptide aptamer technology is relatively youthful. It has the advantage over existing techniques that the reagents identified are designed for expression in eukaryotic cells. This allows the construction of molecular tools that allow the logic of genetics, from knockouts to extragenic suppressors, to be applied to studies of proteins in tissue culture cells. Until recently, the available tools have limited our understanding of cell biology. The same limitation restricts out ability to validate the numerous candidate drug targets emerging from genome-wide approaches to cellular biology. Peptide aptamers represent a stride forwards in the evolution of a modular, molecular tool kit for cell biology and for drug target validation. The authors predict that they will also play a role in the transition from genomic to proteomic microarray technology.

Animals↗

PubMed2000

Plant genome databases: from references to inference tools.

Plant genome databases play an important role in the archiving and dissemination of data arising from the international genome projects. Recent developments in bioinformatics, such as new software tools, programming languages and standards, have produced better access across the Internet to the data held within them. An increasing emphasis is placed on data analysis and indeed many resources now provide tools allied to the databases, to aid in the analysis and interpretation of the data. However, a considerable wealth of information lies untapped by considering the databases as single entities and will only be exploited by linking them with a wide range of data sources. Data from research programs such as comparative mapping and germplasm studies may be used as tools, to gain additional knowledge but without additional experimentation. To date, the current plant genome databases are not yet linked comprehensively with each other or with these additional resources, although they are clearly moving toward this. Here, the current wealth of public plant genome databases is reviewed, together with an overview of initiatives underway to bind them to form a single plant genome infrastructure.

Computational Biology↗

PubMed2003

Comparative genomics tools applied to bioterrorism defence.

Rapid advances in the genomic sequencing of bacteria and viruses over the past few years have made it possible to consider sequencing the genomes of all pathogens that affect humans and the crops and livestock upon which our lives depend. Recent events make it imperative that full genome sequencing be accomplished as soon as possible for pathogens that could be used as weapons of mass destruction or disruption. This sequence information must be exploited to provide rapid and accurate diagnostics to identify pathogens and distinguish them from harmless near-neighbours and hoaxes. The Chem-Bio Non-Proliferation (CBNP) programme of the US Department of Energy (DOE) began a large-scale effort of pathogen detection in early 2000 when it was announced that the DOE would be providing bio-security at the 2002 Winter Olympic Games in Salt Lake City, Utah. Our team at the Lawrence Livermore National Lab (LLNL) was given the task of developing reliable and validated assays for a number of the most likely bioterrorist agents. The short timeline led us to devise a novel system that utilised whole-genome comparison methods to rapidly focus on parts of the pathogen genomes that had a high probability of being unique. Assays developed with this approach have been validated by the Centers for Disease Control (CDC). They were used at the 2002 Winter Olympics, have entered the public health system, and have been in continual use for non-publicised aspects of homeland defence since autumn 2001. Assays have been developed for all major threat list agents for which adequate genomic sequence is available, as well as for other pathogens requested by various government agencies. Collaborations with comparative genomics algorithm developers have enabled our LLNL team to make major advances in pathogen detection, since many of the existing tools simply did not scale well enough to be of practical use for this application. It is hoped that a discussion of a real-life practical application of comparative genomics algorithms may help spur algorithm developers to tackle some of the many remaining problems that need to be addressed. Solutions to these problems will advance a wide range of biological disciplines, only one of which is pathogen detection. For example, exploration in evolution and phylogenetics, annotating gene coding regions, predicting and understanding gene function and regulation, and untangling gene networks all rely on tools for aligning multiple sequences, detecting gene rearrangements and duplications, and visualising genomic data. Two key problems currently needing improved solutions are: (1) aligning incomplete, fragmentary sequence (eg draft genome contigs or arbitrary genome regions) with both complete genomes and other fragmentary sequences; and (2) ordering, aligning and visualising non-colinear gene rearrangements and inversions in addition to the colinear alignments handled by current tools.

Amino Acid Sequence↗

PubMed1994

Hierarchical Access System for Sequence Libraries in Europe (HASSLE): a tool to access sequence databases remotely.

Sequence databases in biology are growing exponentially. Not only are large sites needed to keep the data, but the number of customers is continuously increasing. Network access plays a key role in utilizing remote resources. However, both synchronous and asynchronous access require tools that are currently non-standard in molecular biology computing. Additionally, information discovery of today frequently focuses on centers rather a hierarchically interconnected facilities. HASSLE (Hierarchical Access System for Sequence Libraries in Europe) is an implementation of an application-independent, user-transparent access tool in molecular biology. It features tools for both clients and information providers to permit accounting and/or prioritization on various levels. HASSLE focuses on the network aspect of the molecular biology computing and assumes that it is possible to have database applications available as remote 'services' (programs, program packages or utilities) which can be started by a simple command script after a suitable feed of datafiles. The current system provides these services for searching with programs like FASTA or BLAST which are compiled as obtained from vendors or servers.

Algorithms↗

PubMed1996

HBexplore--a new tool for identifying and analysing hydrogen bonding patterns in biological macromolecules.

The program HBexplore is a new tool for identifying and analysing H-bonding patterns in biological macromolecules. It selects all potential H-bonds according to geometrical criteria. The H-bond table can then be subjected to further automatic or interactive analysis tools. These tools include the calculation of mean values and distributions of geometrical H-bond parameters for parts of a single structure, for complete single structures and for structure sets, the classification of each H-bond according to the participation of backbone, side chain or base, ligand and water parts of nucleic acids or proteins, identification of Watson-Crick nucleotide pairs and of H-bonded pairs of equal nucleotides, the calculation of the mean number of H-bonds per residue, and of the fraction of potential donor and acceptor atoms involved in H-bonds. HBexplore further generates automatically a H-bond residue interaction table. This table lists for all residues of the structure the other residues, ligands or water molecules directly connected via a H-bond. By means of a binary tree search algorithm, this table is then converted into a H-bond cluster table. Clusters are understood here as an uninterrupted network of H-bonded residues. For nucleic acids, secondary structures and tertiary interactions are automatically derived from the H-bonding pattern. HBexplore is applied to two example RNA structures: a pseudoknot and a hairpin. It provides a comprehensive listing of individual H-bonds and statistical information for larger structure sets. In addition, it can identify interesting new H-bond motifs. One example is a pentanucleotide base-base H-bond interaction motif in the RNA pseudoknot. HBexplore is intended to contribute both to the elucidation of general principles of the architecture of biological macromolecules, and to the prediction and refinement of single structures.

Algorithms↗

PubMed1998

Molecules to maps: tools for visualization and interaction in support of computational biology.

The volume of data produced by genome projects, X-ray crystallography, NMR spectroscopy, and electron and confocal microscopy present the bioinformatics community with new challenges for analyzing, understanding, and exchanging this data. At the 1998 Pacific Symposium on Biocomputing, a track entitled 'Molecules to Maps: Tools for Visualization and Interaction in Computational Biology' provided tool developers and users with the opportunity to discuss advances in tools and techniques to assist scientists in evaluating, absorbing, navigating, and correlating this sea of information, through visualization and user interaction. In this paper we present these advances and discuss some of the challenges that remain to be solved.

Computational Biology↗

PubMed1999

Stem Trace: an interactive visual tool for comparative RNA structure analysis.

MOTIVATION: Stem Trace is one of the latest tools available in STRUCTURELAB, an RNA structure analysis computer workbench. The paradigm used in STRUCTURELAB views RNA structure determination as a problem of dealing with a database of a large number of computationally generated structures. Stem Trace provides the capability to analyze this data set in a novel, visually driven, interactive and exploratory way. In addition to providing graphs at a high level of ion, it is also connected with complementary visualization tools which provide orthogonal views of the same data, as well as drawing of structures represented by a stem trace. Thus, on top of being an analysis tool, Stem Trace is a graphical user interface to an RNA structural information database. RESULTS: We illustrate Stem Trace's capabilities with several examples of the analysis of RNA folding data performed on 24 strains of HIV-1, HIV-2 and SIV sequences around the HIV dimerization region. This dimer linkage site has been found to play a role in encapsidation, reverse transcription, recombination, and inhibition of translation. Our examples show how Stem Trace elucidates preservation of structures in this region across the various strains of HIV. AVAILABILITY: The program can be made available upon request. It runs on SUN, SGI and DEC (Compaq) Unix workstations.

Algorithms↗

PubMed1999

ORBIT: an integrated environment for user-customized bioinformatics tools.

MOTIVATION: There are a large number of computational programs freely available to bioinformaticians via a client/server, web-based environment. However, the client interface to these tools (typically an html form page) cannot be customized from the client side as it is created by the service provider. The form page is usually generic enough to cater for a wide range of users. However, this implies that a user cannot set as 'default' advanced program parameters on the form or even customize the interface to his/her specific requirements or preferences. Currently, there is a lack of end-user interface environments that can be modified by the user when accessing computer programs available on a remote server running on an intranet or over the Internet. RESULTS: We have implemented a client/server system called ORBIT (Online Researcher's Bioinformatics Interface Tools) where individual clients can have interfaces created and customized to command-line-driven, server-side programs. Thus, Internet-based interfaces can be tailored to a user's specific bioinformatic needs. As interfaces are created on the client machine independent of the server, there can be different interfaces to the same server-side program to cater for different parameter settings. The interface customization is relatively quick (between 10 and 60 min) and all client interfaces are integrated into a single modular environment which will run on any computer platform supporting Java. The system has been developed to allow for a number of future enhancements and features. ORBIT represents an important advance in the way researchers gain access to bioinformatics tools on the Internet.

Computational Biology↗

PubMed1993

PFGE MAPPER: a tool to aid in the analysis of pulse field gel electrophoresis maps.

Pulse field gel electrophoresis mapping is an important technique for characterizing large segments of DNA and constructing long-range restriction maps. We have developed a tool, PFGE MAPPER, to aid in the construction of pulse field electrophoresis gel maps. This tool helps construct pulse field gel maps from single and double digest experiments visualized by hybridization with single copy probes. The program is written in Think C and runs on Macintosh computers. An intuitive interface allows the user to interactively modify fragment sizes or errors, select fragments for analysis and recalculate the maps. Maps can be printed or saved for later viewing. After constructing and saving several maps in a region, PFGE MAPPER can be used to refine and extend the overall map by merging individual maps. This tool should be useful for constructing long-range restriction maps of genomic DNA and yeast artificial chromosomes.

Algorithms↗

PubMed2025

AdDeam: a fast and scalable tool for estimating and clustering reference-level damage profiles.

MOTIVATION: DNA damage patterns, such as increased frequencies of C→T and G→A substitutions at fragment ends, are widely used in ancient DNA studies to assess authenticity and detect contamination. In metagenomic studies, fragments can be mapped against multiple references or de novo assembled contigs to identify those likely to be ancient. Generating and comparing damage profiles, however, can be both tedious and time-consuming. Although tools exist for estimating damage in single reference genomes and metagenomic datasets, none efficiently cluster damage patterns. RESULTS: To address this methodological gap, we developed AdDeam, a tool that combines rapid damage estimation with clustering for streamlined analyses and easy identification of potential contaminants or outliers. Our tool takes aligned ancient DNA (aDNA) fragments from various samples or contigs as input, computes damage patterns, clusters them, and outputs representative damage profiles per cluster, a probability of each sample pertaining to a cluster, as well as a Principal Component Analysis of the damage patterns for each sample for fast visualisation. We evaluated AdDeam on both simulated and empirical datasets. AdDeam effectively distinguishes different damage levels, such as uracil-DNA glycosylase-treated samples, sample-specific damages from specimens of different time periods, and can also distinguish between contigs containing modern or ancient fragments, providing a clear framework for aDNA authentication and facilitating large-scale analyses. AVAILABILITY AND IMPLEMENTATION: AdDeam is publicly available at https://github.com/LouisPwr/AdDeam and can also be installed via Bioconda. It is implemented in Python and C++. All analysis scripts and datasets are available at https://github.com/LouisPwr/AdDeamAnalysis and on Zenodo under: 10.5281/zenodo.15052427.

Software↗

PubMed2025

Pedigree Painter (pepa): a tool for the visualization of genetic inheritance in chromosomal context.

MOTIVATION: Data visualization is increasingly important in genomics, enabling researchers to uncover inheritance and recombination patterns across generations. While most existing tools focus on ancestry prediction, they lack functionality for analyzing known ancestries in controlled settings, such as determining parental contributions to offspring genomes. To address this gap, I developed pepa, a lightweight, deterministic, modular tool that visualizes and quantifies genomic inheritance, designed for beginner and advanced users. RESULTS: pepa is a program for processing VCF files, assigning ancestries to homozygous SNPs, and clustering them into biologically meaningful regions. It generates human-readable comparison tables and visualizes inheritance patterns with chromosome paintings through R. Tested on fission yeast, pepa revealed non-uniform recombination patterns, with chromosomes largely inherited from one parent and seemingly random recombination. Quantitative analyses showed differences in parental contributions at the nucleotide and gene levels, with some offspring inheriting similar percentages from parents. However, the painted chromosomes revealed that even offspring with similar percentages from one parent rarely inherit the same genomic region, highlighting the importance of this tool in drawing biologically meaningful insights. pepa provides an accessible and powerful solution for analyzing genomic inheritance, bridging experimental and computational biology. Its modular design and minimal dependencies allow adaptation to diverse organisms, facilitating intuitive visualization and quantitative insights into recombination dynamics.

Pedigree↗

PubMed2025

UMI-nea: a fast, robust tool for reference-free UMI deduplication and accurate quantification.

MOTIVATION: One of the key applications of Unique Molecular Identifiers (UMIs) in high-throughput sequencing is to correct for PCR amplification bias and removal of PCR duplicates, thereby improving quantification in DNA-seq and RNA-seq applications. Accurately grouping error-bearing UMIs that originate from the same input molecule through a UMI deduplication method is a critical step in this process. However, many existing UMI deduplication tools rely on simple Hamming distance comparisons or suboptimal clustering algorithms, often resulting in erroneous UMI groupings, particularly in error-prone long-read sequencing or ultra-high-depth short-read sequencing. RESULTS: We introduce UMI-nea, a tool that utilizes Levenshtein distance comparisons and a novel clustering approach to optimize multithreading workflows. Compared against three other indel-aware UMI deduplication tools, UMI-nea achieves more accurate UMI groupings with efficient run time. It demonstrates robust performance across diverse sequencing platforms, depths, and UMI lengths. Additionally, UMI-nea incorporates a data-guided adaptive UMI filter, further enhancing quantification accuracy. AVAILABILITY AND IMPLEMENTATION: UMI-nea is available on github https://github.com/Qiaseq-research/UMI-nea.git or Zenodo https://doi.org/10.5281/zenodo.16745758. Sequencing data are stored at https://qiagenpublic.blob.core.windows.net/umi-nea-datasets/.

High-Throughput Nucleotide Sequencing↗

PubMed2025

SPARKI: a tool for the statistical analysis of pathogen identification results.

MOTIVATION: Many pathogen identification and microbiome analysis tools have been developed in recent years, with Kraken 2 being one of the most popular. While tools downstream of Kraken 2 can assist in the interpretation of its outputs, a statistical framework to assess the likelihood that a taxon/organism is present in a single sample alongside an automated end-to-end analysis pipeline has not yet been fully implemented. RESULTS: Here, we introduce SPARKI, an R package that performs statistical analysis of Kraken 2 outputs and aids in the identification of pathogens present in next-generation sequencing samples. SPARKI adds to the field by bringing a probabilistic view to Kraken 2 data, serving as a discovery tool and complementing other methods such as KrakenTools, Bracken, and Pavian. AVAILABILITY AND IMPLEMENTATION: SPARKI code is available on GitHub at https://github.com/team113sanger/sparki. SPARKI is also part of an end-to-end pathogen identification pipeline, sparki-nf, which is available at https://github.com/team113sanger/sparki-nf. An additional pipeline for further exploration and validation of SPARKI results is also available at https://github.com/team113sanger/map-to-genome.

Software↗

PubMed2026

ChemGenXplore: an interactive tool for exploring and analysing chemical genomic data.

MOTIVATION: Chemical genomics is a powerful high-throughput approach to systematically link phenotypes to genotypes. However, the vast datasets generated remain challenging to explore due to the lack of integrated, interactive tools for visualization and analysis. Existing workflows often require multiple independent software tools, limiting data accessibility and collaboration. Therefore, we created a user-friendly platform that enables efficient exploration and sharing of chemical genomics data. RESULTS: We developed ChemGenXplore, a web-based Shiny application designed to streamline the visualization and analysis of chemical genomic screens. It offers two primary functionalities: one for exploring pre-implemented datasets and another for analysing user-uploaded datasets. ChemGenXplore enables users to visualize phenotypic profiles, assess gene-gene and condition-condition correlations, perform GO and KEGG enrichment analysis, and generate customizable, interactive heatmaps. To further support collaborative research, ChemGenXplore also facilitates the comparative analysis of chemical genomic and other omics datasets. By consolidating these features into a single interactive and accessible tool, ChemGenXplore facilitates data sharing, enhances reproducibility, and promotes collaboration within the research community. AVAILABILITY AND IMPLEMENTATION: ChemGenXplore is freely accessible as a web application at https://chemgenxplore.kaust.edu.sa/. Source code and documentation, including instructions for local installation, are provided on GitHub (https://github.com/Hudaahmadd/ChemGenXplore). A Docker image is also available on DockerHub (https://hub.docker.com/r/hudaahmad/chemgenxplore) to ensure reproducibility and simplify installation.

Software↗

PubMed2026

Yomix: an interactive tool for the exploration of low-dimensional embeddings in omics data.

SUMMARY: In the analysis of diverse omics data, a common and important preliminary step involves computing low-dimensional embeddings using techniques such as PCA, UMAP, t-SNE, or variational autoencoders. These embeddings provide a global overview of sample distributions and their relationships, often serving as the basis for formulating biological hypotheses. To facilitate rapid and intuitive exploration of such low-dimensional embeddings, we developed Yomix, an interactive omics-agnostic visualization and data exploration tool. Yomix enables users to flexibly define subsets of interest using a lasso selection tool, instantly compute their feature signatures, and compare their distributions. Yomix is a fast and efficient tool for interactive exploration of diverse omics datasets. AVAILABILITY AND IMPLEMENTATION: Yomix and its documentation are publicly available at https://github.com/perrin-isir/yomix.

Software↗