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PubMed2006

Systematic analysis of Arabidopsis organelles and a protein localization database for facilitating fluorescent tagging of full-length Arabidopsis proteins.

Cells are organized into a complex network of subcellular compartments that are specialized for various biological functions. Subcellular location is an important attribute of protein function. To facilitate systematic elucidation of protein subcellular location, we analyzed experimentally verified protein localization data of 1,300 Arabidopsis (Arabidopsis thaliana) proteins. The 1,300 experimentally verified proteins are distributed among 40 different compartments, with most of the proteins localized to four compartments: mitochondria (36%), nucleus (28%), plastid (17%), and cytosol (13.3%). About 19% of the proteins are found in multiple compartments, in which a high proportion (36.4%) is localized to both cytosol and nucleus. Characterization of the overrepresented Gene Ontology molecular functions and biological processes suggests that the Golgi apparatus and peroxisome may play more diverse functions but are involved in more specialized processes than other compartments. To support systematic empirical determination of protein subcellular localization using a technology called fluorescent tagging of full-length proteins, we developed a database and Web application to provide preselected green fluorescent protein insertion position and primer sequences for all Arabidopsis proteins to study their subcellular localization and to store experimentally verified protein localization images, videos, and their annotations of proteins generated using the fluorescent tagging of full-length proteins technology. The database can be searched, browsed, and downloaded using a Web browser at http://aztec.stanford.edu/gfp/. The software can also be downloaded from the same Web site for local installation.

Arabidopsis↗

PubMed2003

Matrix2png: a utility for visualizing matrix data.

UNLABELLED: We describe a simple software tool, 'matrix2png', for creating color images of matrix data. Originally designed with the display of microarray data sets in mind, it is a general tool that can be used to make simple visualizations of matrices for use in figures, web pages, slide presentations and the like. It can also be used to generate images 'on the fly' in web applications. Both continuous-valued and discrete-valued (categorical) data sets can be displayed. Many options are available to the user, including the colors used, the display of row and column labels, and scale bars. In this note we describe some of matrix2png's features and describe some places it has been useful in the authors' work. AVAILABILITY: A simple web interface is available, and Unix binaries are available from http://microarray.cpmc.columbia.edu/matrix2png. Source code is available on request.

Color↗

PubMed2004

Isotopica: a tool for the calculation and viewing of complex isotopic envelopes.

The web application Isotopica has been developed as an aid to the interpretation of ions that contain naturally occurring isotopes in a mass spectrum. It allows the calculation of mass values and isotopic distributions based on molecular formulas, peptides/proteins, DNA/RNA, carbohydrate sequences or combinations thereof. In addition, Isotopica takes modifications of the input molecule into consideration using a simple and flexible language as a straightforward extension of the molecular formula syntax. This function is especially useful for biomolecules, which are often subjected to additional modifications other than normal constituents, such as the frequently occurring post-translational modification in proteins. The isotopic distribution of any molecule thus defined can be calculated by considering full widths at half maximum or mass resolution. The combined envelope of several overlapping isotopic distributions of a mixture of molecules can be determined after specifying each molecule's relative abundance. The results can be displayed graphically on a local PC using the Isotopica viewer, a standalone application that is downloadable from the sites below, as a complement to the client browser. The m/z and intensity values can also be obtained in the form of a plain ASCII text file. The software has proved to be useful for peptide mass fingerprinting and validating an observed isotopic ion distribution with reference to the theoretical one, even from a multi-component sample. The web server can be accessed at http://bioinformatica.cigb.edu.cu/isotopica and http://coco.protein.osaka-u.ac.jp/isotopica [correction].

Amino Acid Sequence↗

PubMed2004

Gene ontology application to genomic functional annotation, statistical analysis and knowledge mining.

While a massive amount of biomolecular information is increasingly accumulating in different databanks, on the other hand high-throughput technologies are generating a great quantity of data that need to be annotated with the genomic information available, and interpreted. To this aim, the use of specific ontologies can greatly help either in integrating different information stored within heterogeneous databanks, or in identifying and clustering sequence data sharing common characteristics. In the molecular biology domain, the Gene Ontology (GO) is the most developed and widely used ontology. To demonstrate its great utility in the annotation and biological interpretation of gene sets obtained by means of high-throughput experiments, we implemented the web application here described. It enables functional annotations of a given gene set on a genomic scale and across different species. Within our application the annotations provided by the GO vocabulary allow either to easily bind several information from different resources, or to cluster annotated genes according to their biological characteristics. Through the GO structure it is also possible to represent biological concepts with different specificity levels, from very general to very precise concepts. Furthermore, the statistical evaluation of the categorizations provided by the GO annotations enables to highlight the most significant biological characteristics of a gene set, and therefore to mine knowledge from data. Our created tool meets the need to manage a vast quantity of biological data with a simple user interface adapt also for users with limited informatics knowledge, leading them to evaluate the functional significance of experiment's results with graphical views and statistical indexes in a well-known web browser user interface.

Genomics↗

PubMed2006

The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System--a one-stop gateway to online bioinformatics databases and software tools.

To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine, which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site (http://www.hsls.pitt.edu/guides/genetics/obrc).

Computational Biology↗

PubMed2005

A decade devoted to improving online health information quality.

Created in 1995 in response to consumer enthusiasm for the World Wide Web, Health On the Net FoundationHealth On the Net Foundation: http://www.healthonnet.org/ has developed solutions to address the problem of potentially dangerous online health and medical information. Then as now, no international legal framework regulated online content, and consumers needed to be given the means to check the reliability and the relevance of health information [[1]]. HON was first to introduce a code of conduct for online health and medical publishers, the HONcode [[2],[3],[4]], which was readily adopted by webmasters aware of the need for credibility in the new, competitive online space. HON went on to develop Web applications to enhance access to reliable information, making use of innovative NLP-based and semantic search technologies.This paper describes the implementation of a quality standard for online information (HONcode) based on the information production process; its evolution through nearly 10 years of effectiveness, its challenges and results. Today, over 4,700 HON-accredited websites, respecting minimum standards for disclosure and responsibility in online medical publishing, constitute the largest voluntary accreditation network on the Web.

Consumer Health Information↗

PubMed2005

TRAMPLE: the transmembrane protein labelling environment.

TRAMPLE (http://gpcr.biocomp.unibo.it/biodec/) is a web application server dedicated to the detection and the annotation of transmembrane protein sequences. TRAMPLE includes different state-of-the-art algorithms for the prediction of signal peptides, transmembrane segments (both beta-strands and alpha-helices), secondary structure and fast fold recognition. TRAMPLE also includes a complete content management system to manage the results of the predictions. Each user of the server has his/her own workplace, where the data can be stored, organized, accessed and annotated with documents through a simple web-based interface. In this manner, TRAMPLE significantly improves usability with respect to other more traditional web servers.

Algorithms↗

PubMed2004

TROD: T7 RNAi Oligo Designer.

We have developed T7 RNAi Oligo Designer (TROD), a web application for RNA interference studies. TROD greatly facilitates the design of oligodeoxynucleotide sequences for the in vitro production of siRNA duplexes with T7 RNA polymerase. Given a query cDNA sequence, the program scans for appropriate target sequences based on the constraints of the T7 RNA polymerase method and published criteria for RNA interference with siRNAs. The output is an ordered and prioritized list of ready-to-order DNA oligonucleotide sequences, with links to perform a BLAST search to ascertain target sequence specificity. The TROD web service is available at http://www.cellbio.unige.ch/RNAi.html.

DNA-Directed RNA Polymerases↗

PubMed2004

ESTIMA, a tool for EST management in a multi-project environment.

BACKGROUND: Single-pass, partial sequencing of complementary DNA (cDNA) libraries generates thousands of chromatograms that are processed into high quality expressed sequence tags (ESTs), and then assembled into contigs representative of putative genes. Usually, to be of value, ESTs and contigs must be associated with meaningful annotations, and made available to end-users. RESULTS: A web application, Expressed Sequence Tag Information Management and Annotation (ESTIMA), has been created to meet the EST annotation and data management requirements of multiple high-throughput EST sequencing projects. It is anchored on individual ESTs and organized around different properties of ESTs including chromatograms, base-calling quality scores, structure of assembled transcripts, and multiple sources of comparison to infer functional annotation, Gene Ontology associations, and cDNA library information. ESTIMA consists of a relational database schema and a set of interactive query interfaces. These are integrated with a suite of web-based tools that allow a user to query and retrieve information. Further, query results are interconnected among the various EST properties. ESTIMA has several unique features. Users may run their own EST processing pipeline, search against preferred reference genomes, and use any clustering and assembly algorithm. The ESTIMA database schema is very flexible and accepts output from any EST processing and assembly pipeline. ESTIMA has been used for the management of EST projects of many species, including honeybee (Apis mellifera), cattle (Bos taurus), songbird (Taeniopygia guttata), corn rootworm (Diabrotica vergifera), catfish (Ictalurus punctatus, Ictalurus furcatus), and apple (Malus x domestica). The entire resource may be downloaded and used as is, or readily adapted to fit the unique needs of other cDNA sequencing projects. CONCLUSIONS: The scripts used to create the ESTIMA interface are freely available to academic users in an archived format from http://titan.biotec.uiuc.edu/ESTIMA/. The entity-relationship (E-R) diagrams and the programs used to generate the Oracle database tables are also available. We have also provided detailed installation instructions and a tutorial at the same website. Presently the chromatograms, EST databases and their annotations have been made available for cattle and honeybee brain EST projects. Non-academic users need to contact the W.M. Keck Center for Functional and Comparative Genomics, University of Illinois at Urbana-Champaign, Urbana, IL, for licensing information.

Animals↗

PubMed2026

shinyDeepGxP: a user-friendly R shiny app for predicting surface protein abundance from scRNA-seq expression using deep learning in blood cells.

MOTIVATION: Understanding accurate immune cell heterogeneity and function in single-cell datasets requires access to protein-level information, which is often unavailable due to experimental limitations. RESULTS: We present shinyDeepGxP, an interactive web application featuring our deep learning model, DeepGxP, for predicting surface protein abundance from single-cell RNA-sequencing (scRNA-seq) data. This platform makes DeepGxP accessible to researchers without programming skills. Users can upload scRNA-seq count matrices and use "Predict Protein" to predict the abundance of 224 biologically relevant surface proteins. shinyDeepGxP provides visualizations to help identify distinct cell populations based on predicted protein profiles. Moreover, users can choose "Explore Model" to reveal key RNA predictors and their associated biological pathways for each protein. Overall, shinyDeepGxP is a user-friendly, freely available web tool that provides protein-level detail for RNA-only single-cell datasets, enabling multimodal discovery without additional experiments. AVAILABILITY AND IMPLEMENTATION: shinyDeepGxP can be launched on https://shiny.crc.pitt.edu/deepgxp/.

Journal Article↗

PubMed2005

Using simulation to assess the sensitivity and specificity of a signal detection tool for multidimensional public health surveillance data.

The objective of the work described in this paper is to develop a means for characterizing the validity of an empirical methodology for detecting signals potentially related to complicated adverse event (AE) coding terms in multidimensional public health surveillance data. The signal detection tool under evaluation is the multi-item gamma Poisson shrinkage (MGPS) estimation program. We were interested in its potential application to passive surveillance system monitoring, to screen for 'signals' of complicated adverse event coding terms (AE terms) in complex and noisy data. The research was to design and produce a flexible and user-friendly utility for probabilistically defining complicated signals in a database, iterating large numbers of applications of the MGPS detection algorithm and establishing proportions of correct detection events. We sought to establish the specificity of the MGPS by developing a random background using a gradient that ranged from rigorous (but not very relevant) to relevant (but noisy). To establish the sensitivity, signals were defined based on recognized public health issues of interest (such as the introduction of a new vaccine into the population). Methods of representing a signal included a simple pair-wise association consisting of a new vaccine and one AE term, as well as a more realistic complex of multiple AE terms comprising a 'syndrome'. A web application has been developed to create and insert signals with user-defined probabilities in multiple iterations of simulated random background data. Three forms of simulated data based on the vaccine adverse event reporting system (VAERS) cumulative spontaneous database were defined to serve as background noise against which to contrast introduced vaccine adverse event signals: (1) completely random associations between vaccines and AE terms, (2) random associations of vaccine sets and AE term sets preserving naturally observed vaccine co-occurrences and AE term co-occurrences and (3) samples from the actual VAERS data as reported. Rates of detection by the MGPS algorithm can be established for specific signal patterns at varying probabilistic intensities in a choice of random background data forms. Knowing these rates is important for determining the degree of response to an MGPS signal detection event in 'live' data.

Computer Simulation↗

PubMed2005

Rapid application design of an electronic clinical skills portfolio for undergraduate medical students.

The aim was to find how to use information and communication technology to present the clinical skills content of an undergraduate medical curriculum. Rapid application design was used to develop the product, and technical action research was used to evaluate the development process. A clinician-educator, two medical students, two computing science masters students, two other project workers, and a hospital education informatics lead, formed a design team. A sample of stakeholders took part in requirements planning workshops and continued to advise the team throughout the project. A university hospital had many features that favoured fast, inexpensive, and successful system development: a clearly defined and readily accessible user group; location of the development process close to end-users; fast, informal communication; leadership by highly motivated and senior end-users; devolved authority and lack of any rigidly imposed management structure; cooperation of clinicians because the project drew on their clinical expertise to achieve scholastic goals; a culture of learning and involvement of highly motivated students. A detailed specification was developed through storyboarding, use case diagramming, and evolutionary prototyping. A very usable working product was developed within weeks. "SkillsBase" is a database web application using Microsoft Active Server Pages, served from a Microsoft Windows 2000 Server operating system running Internet Information Server 5.0. Graphing functionality is provided by the KavaChart applet. It presents the skills curriculum, provides a password-protected portfolio function, and offers training materials. The curriculum can be presented in several different ways to help students reflect on their objectives and progress towards achieving them. The reflective portfolio function is entirely private to each student user and allows them to document their progress in attaining skills, as judged by self, peer and tutor assessment, and examinations. Training materials include web links and materials developed locally using pedagogic principles developed by the SkillsBase team. Although the usability of SkillsBase has been proven, uptake of software that has arisen 'bottom-up' from within the curriculum has proved slow. We plan to incorporate the SkillsBase services into a more comprehensive virtual managed learning environment, anticipating that presenting the functionality in an environment that is routinely used by students and teachers will increase uptake and use.

Clinical Competence↗

PubMed2005

OxfordGrid: a web interface for pairwise comparative map views.

SUMMARY: OxfordGrid is a web application and database schema for storing and interactively displaying genetic map data in a comparative, dot-plot, fashion. Its display is composed of a matrix of cells, each representing a pairwise comparison of mapped probe data for two linkage groups or chromosomes. These are arranged along the axes with one forming grid columns and the other grid rows with the degree and pattern of synteny/colinearity between the two linkage groups manifested in the cell's dot density and structure. A mouse click over the selected grid cell launches an image map-based display for the selected cell. Both individual and linear groups of mapped probes can be selected and displayed. Also, configurable links can be used to access other web resources for mapped probe information. AVAILABILITY: OxfordGrid is implemented in C#/ASP.NET and the package, including MySQL schema creation scripts, is available at ftp://cggc.agtec.uga.edu/OxfordGrid/.

Algorithms↗

PubMed2025

PoweREST: Statistical power estimation for spatial transcriptomics experiments to detect differentially expressed genes between two conditions.

Recent advancements in spatial transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost for current ST data generation techniques restricts the large-scale application of ST. Consequently, maximization of the use of available resources to achieve robust statistical power for ST data is a pressing need. One fundamental question in ST analysis is detection of differentially expressed genes (DEGs) under different conditions using ST data. Such DEG analyses are performed frequently, but their power calculations are rarely discussed in the literature. To address this gap, we developed PoweREST, a power estimation tool designed to support the power calculation for DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments and after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application that allows users to interactively calculate and visualize study power along with relevant parameters.

Gene Expression Profiling↗

PubMed2026

MaizeGDB Phylostrata Tool: exploring evolutionary origins of maize proteins.

MOTIVATION: Phylostratigraphic analysis identifies the evolutionary origins and level of conservation of proteins, facilitating research in evolutionary biology and comparative genomics. RESULTS: We developed the MaizeGDB Phylostrata Tool, a custom web application that enables users to explore the evolutionary origins of proteins in maize (Zea mays), a globally important crop and model organism. This tool features interactive visualizations and detailed gene pages incorporating subcellular localization, Gene Ontology (GO) terms, and links to resources for homologs, facilitating comparison of gene functions across evolutionary time. The tool also provides downloadable links for full-proteome phylostratigraphic results for 26 maize inbreds (B73 and the NAM founders). From these, we identified genome- and subgenome-wide trends, finding that more conserved proteins tended to be longer and more highly expressed. Finally, we provide code including updates to the "phylostratr" R package to make it more robust against taxonomic updates, as well as example scripts for phylostratigraphic analysis and web tool development for researchers and curators of other species. AVAILABILITY AND IMPLEMENTATION: The MaizeGDB Phylostrata Tool is freely available at https://phylostrata.maizegdb.org. Scripts used for the analysis and web tool are available at https://github.com/LTibbs/PhylostrataWebtool.

Journal Article↗

PubMed2024

PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions.

Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.

Differentially expressed genes↗

PubMed2026

Discovery and validation of a multi-protein panel for predicting non-fatal major adverse cardiovascular events in diabetic kidney disease.

OBJECTIVE: To identify plasma protein biomarkers associated with incident non-fatal major adverse cardiovascular events (MACE) in diabetic kidney disease (DKD) patients. RESEARCH DESIGN AND METHODS: We analyzed 317 DKD patients from the UK Biobank. Plasma proteomics and clinical data (demographics, metabolism, renal function) were integrated. In an exploratory discovery phase, three sequential Cox regression models (crude, socio-demographic-adjusted, socio-demographic-metabolic adjusted) screened non-fatal MACE-associated proteins. To prevent information leakage, the cohort was then randomly split into training (70%) and testing (30%) sets; machine-learning feature selection, hyperparameter optimization, and final model development were performed exclusively within the training set. The associated proteins were input into the four-step machine-learning pipeline (LASSO-Cox, random survival forest, Boruta, XGBoost-Cox). Predictive performance was validated using Kaplan-Meier survival analyses, longitudinal trajectory modeling, and ROC benchmarking. An interactive web application was deployed for clinical implementation. RESULTS: Of 1,463 plasma proteins, 561 were associated with non-fatal MACE across Cox models, with 14 overlapping proteins. Nine core proteins (ANG, IL1R1, CXCL14, ESAM, PTGDS, HAVCR1, FGFR2, IGSF8, CCL3) were validated: ANG showed the strongest non-fatal MACE association (HR = 3.88, 95%CI 2.33-6.48, p<0.001), and all high-expression groups had elevated non-fatal MACE risk. GO/KEGG enrichment highlighted inflammatory-immune pathways like positive regulation of MAPK cascade, Cytokine-cytokine receptor interaction and PI3K-Akt signaling pathway as key mechanisms. The model integrating proteins, demographic factors, and clinical variables achieved the highest predictive performance across non-fatal MACE (AUC = 0.768), myocardial infarction (MI) (0.808), and stroke (0.816) outcomes, with superior stability in cross-validation. CoxBoost + Elastic Net framework was selected as the optimal framework via benchmarking of 101 algorithms. The model demonstrated favorable calibration in high-risk patients and yielded positive net clinical benefit across decision thresholds of 5% to 45%. The web tool (https://jiangli2941.github.io/MACE-prediction-v2/) enables input of 28 variables, outputs non-fatal MACE risk status, risk probability, and highlights abnormal indicators. CONCLUSION: Plasma proteomics combined with machine learning identifies robust non-fatal MACE predictors in DKD.

Humans↗

PubMedDate not supplied

Developing secure Web-based medical applications.

The EUROMED-ETS pilot system offers a number of security functionalities using off-the-shelf available products, in order to protect Web-based medical applications. The basic concept used by the proposed security architecture is the Trusted Third Party (TTP). A TTP is used in order to generate, distribute and revoke digital certificates to medical practitioners and healthcare organizations that wish to communicate securely. Digital certificates and digital signatures are used to provide peer and data origin authentication and access control. The paper demonstrates how TTPs can be used effectively in order to develop medical applications that run securely over the World Wide Web.

Algorithms↗