GENEVESTIGATOR. Arabidopsis microarray database and analysis toolbox

High-throughput gene expression analysis has become a frequent and powerful research tool in biology. At present, however, few software applications have been developed for biologists to query large microarray gene expression databases using a Web-browser interface. We present GENEVESTIGATOR, a database and Web-browser data mining interface for Affymetrix GeneChip data. Users can query the database to retrieve the expression patterns of individual genes throughout chosen environmental conditions, growth stages, or organs. Reversely, mining tools allow users to identify genes specifically expressed during selected stresses, growth stages, or in particular organs. Using GENEVESTIGATOR, the gene expression profiles of more than 22,000 Arabidopsis genes can be obtained, including those of 10,600 currently uncharacterized genes. The objective of this software application is to direct gene functional discovery and design of new experiments by providing plant biologists with contextual information on the expression of genes. The database and analysis toolbox is available as a community resource at https://www.genevestigator.ethz.ch.     

CellDepot: A Unified Repository for scRNA-seq Data and Visual Exploration

CellDepot containing over 270 datasets from 8 species and many tissues serves as an integrated web application to empower scientists in exploring single-cell RNA-seq (scRNA-seq) datasets and comparing the datasets among various studies through a user-friendly interface with advanced visualization and analytical capabilities. To begin with, it provides an efficient data management system that users can upload single cell datasets and query the database by multiple attributes such as species and cell types. In addition, the graphical multi-logic, multi-condition query builder and convenient filtering tool backed by MySQL database system, allows users to quickly find the datasets of interest and compare the expression of gene(s) across these. Moreover, by embedding the cellxgene VIP tool, CellDepot enables fast exploration of individual dataset in the manner of interactivity and scalability to gain more refined insights such as cell composition, gene expression profiles, and differentially expressed genes among cell types by leveraging more than 20 frequently applied plotting functions and high-level analysis methods in single cell research. In summary, the web portal available at http://celldepot.bxgenomics.com, prompts large scale single cell data sharing, facilitates meta-analysis and visualization, and encourages scientists to contribute to the single-cell community in a tractable and collaborative way. Finally, CellDepot is released as open-source software under MIT license to motivate crowd contribution, broad adoption, and local deployment for private datasets.     

A database for the analysis of immunity genes in Drosophila

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.     

Oncomine数据库在肿瘤研究中的应用

Oncomine 是目前世界上最大的癌基因芯片数据库和综合数据挖掘平台之一,该数据库整合了GEO、TCGA和已发表文献来源的RNA和DNA-seq数据。数据库目前含有715个基因表达数据集（datasheet）、86 733个人体肿瘤组织和正常组织样本的信息,且有新的数据不断更新。Oncomine 数据库囊括的肿瘤类型有19种,包括：膀胱癌、脑/中枢神经系统肿瘤、乳腺癌、宫颈癌、结直肠癌、食管癌、胃癌、头/颈肿瘤、肾癌、白血病、肝癌、肺癌、淋巴瘤、黑色素瘤、骨髓瘤、卵巢癌、胰腺癌、前列腺癌、肉瘤。本文就如何利用Oncomine数据库,进行肿瘤组织中癌基因表达差异性分析以及基因共表达分析、癌基因在肿瘤组织中的表达及拷贝数分析、多组研究数据集的荟萃分析（meta analysis）、以及癌基因表达与患者生存率关系等进行分析。通过该数据库可以对肿瘤癌基因进行研究前的筛查,有利于发现新的肿瘤生物标记物或治疗靶点,为临床科学研究奠定一定的理论基础。     

The BioGRID database: A comprehensive biomedical resource of curated protein,genetic, and chemical interactions

The BioGRID (Biological General Repository for Interaction Datasets, thebiogrid.org ) is an open‐access database resource that houses manually curated protein and genetic interactions from multiple species including yeast, worm, fly, mouse, and human. The ~1.93 million curated interactions in BioGRID can be used to build complex networks to facilitate biomedical discoveries, particularly as related to human health and disease. All BioGRID content is curated from primary experimental evidence in the biomedical literature, and includes both focused low‐throughput studies and large high‐throughput datasets. BioGRID also captures protein post‐translational modifications and protein or gene interactions with bioactive small molecules including many known drugs. A built‐in network visualization tool combines all annotations and allows users to generate network graphs of protein, genetic and chemical interactions. In addition to general curation across species, BioGRID undertakes themed curation projects in specific aspects of cellular regulation, for example the ubiquitin‐proteasome system, as well as specific disease areas, such as for the SARS‐CoV‐2 virus that causes COVID‐19 severe acute respiratory syndrome. A recent extension of BioGRID, named the Open Repository of CRISPR Screens (ORCS, orcs.thebiogrid.org ), captures single mutant phenotypes and genetic interactions from published high throughput genome‐wide CRISPR/Cas9‐based genetic screens. BioGRID‐ORCS contains datasets for over 1,042 CRISPR screens carried out to date in human, mouse and fly cell lines. The biomedical research community can freely access all BioGRID data through the web interface, standardized file downloads, or via model organism databases and partner meta‐databases.     

MENT: Methylation and expression database of normal and tumor tissues

Integrated analysis of DNA methylation and gene expression can reveal specific epigenetic patterns that are important during carcinogenesis. We built an integrated database of DNA methylation and gene expression termed MENT (Methylation and Expression database of Normal and Tumor tissues) to provide researchers information on both DNA methylation and gene expression in diverse cancers. It contains integrated data of DNA methylation, gene expression, correlation of DNA methylation and gene expression in paired samples, and clinicopathological conditions gathered from the GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas). A user-friendly interface allows users to search for differential DNA methylation by either ‘gene search’ or ‘dataset search’. The ‘gene search’ returns which conditions are differentially methylated in a gene of interest, while ‘dataset search’ returns which genes are differentially methylated in a condition of interest based on filtering options such as direction, DM (differential methylation value), and p-value. MENT is the first database which provides both DNA methylation and gene expression information in diverse normal and tumor tissues. Its user-friendly interface allows users to easily search and view both DNA methylation and gene expression patterns. MENT is freely available at http://mgrc.kribb.re.kr:8080/MENT/.     

A database for the analysis of immunity genes in Drosophila: PADMA database

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.     

There's no place like WormBase: an indispensable resource for Caenorhabditis elegans researchers

The nematode Caenorhabditis elegans is used extensively by scientists to study a wide variety of biological processes and is one of the most thoroughly characterized animals. Over the years, the community of C. elegans researchers has generated a wealth of information on the genetics, development, behaviour, and cellular and molecular biology of the worm. This body of data has grown even larger with the recent application of high throughput screening methodology to study gene function, expression and interactions. WormBase (http://www.wormbase.org) is the primary online source of biological data on C. elegans and related nematodes. Equipped with an assortment of powerful search tools, WormBase allows users to quickly extract a variety of information, including data on individual genes, DNA sequence, cell lineage and literature citations. As the database is well maintained and the functionalities constantly modified in response to evolving researcher needs, WormBase has become a vital component of the laboratories studying the worm and a model for other biological databases.     

基因芯片与植物基因差异表达分析

基因芯片为研究植物不同个体或物种之间以及同一个体在不同生长发育阶段、正常和疾病状态下基因表达的差异、某一性状多基因的协同作用,寻找和定位新的目的基因等方面带来了革命性的变革。与传统研究基因差异表达的方法相比,它具有微型化、用材少、快速、准确、灵敏度能高基、在因同等一研究方面已取得了显著的成绩,如拟南芥、酵母、水稻等。     

Sebida: a database for the functional and evolutionary analysis of genes with sex-biased expression

We describe Sebida, a database of genes with sex-biased expression. The database integrates results from multiple, independent microarray studies comparing male and female gene expression in Drosophila melanogaster, Drosophila simulans and Anopheles gambiae. Sebida uses standard nomenclature, which allows individual genes to be compared across different microarray platforms and to be queried by gene name, symbol, or annotation number. In addition to ratios of male/female expression for each gene, Sebida also contains information useful for evolutionary studies, such as local recombination rate, degree of codon bias and interspecific divergence at synonymous and non-synonymous sites. AVAILABILITY: Sebida can be accessed at http://www.sebida.de     

The Arabidopsis Information Resource (TAIR): a model organism database providing a centralized,curated gateway to Arabidopsis biology,research materials and community

Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system.