UNLABELLED: : Visualizing genes' structure and annotated features helps biologists to investigate their function and evolution intuitively. The Gene Structure Display Server (GSDS) has been widely used by more than 60 000 users since its first publication in 2007. Here, we reported the upgraded GSDS 2.0 with a newly designed interface, supports for more types of annotation features and formats, as well as an integrated visual editor for editing the generated figure. Moreover, a user-specified phylogenetic tree can be added to facilitate further evolutionary analysis. The full source code is also available for downloading. AVAILABILITY AND IMPLEMENTATION: Web server and source code are freely available at http://gsds.cbi.pku.edu.cn. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

With the development of the Internet and the growth of online resources, bioinformatics training for wet-lab biologists became necessary as a part of their education. This article describes a one-semester course 'Applied Bioinformatics Course' (ABC, http://abc.cbi.pku.edu.cn/) that the author has been teaching to biological graduate students at the Peking University and the Chinese Academy of Agricultural Sciences for the past 13 years. ABC is a hands-on practical course to teach students to use online bioinformatics resources to solve biological problems related to their ongoing research projects in molecular biology. With a brief introduction to the background of the course, detailed information about the teaching strategies of the course are outlined in the 'How to teach' section. The contents of the course are briefly described in the 'What to teach' section with some real examples. The author wishes to share his teaching experiences and the online teaching materials with colleagues working in bioinformatics education both in local and international universities.

Jingchu Luo is a Professor in the College of Life Sciences and Center for Bioinformatics, Peking University, China. He is the EMBnet China Node manager and a long-term friend of Jack Leunissen. Harm Nijveen is a scientific programmer at Wageningen University and Research Center, the Netherlands. He had been working with Jack Leunissen for several years. Teresa Attwood is a Professor of Bioinformatics in the Faculty of Life Sciences and School of Computer Science at the University of Manchester, UK. She is the current Chair of the EMBnet Executive Board. David Judge is a bioinformatics trainer in Cambridge University and a long-term friend of Jack Leunissen. Sandor Pongor is a Group Leader of Protein Structure and Bioinformatics, the International Center for Genetic Engineering and Biotechnology (ICGEB), Italy. He organized bioinformatics courses every June in ICGEB. David Landsman is Chief of the Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health. Martin Bishop is the Managing Editor of Briefings in Bioinformatics. It has already been a year since Jack Leunissen, a former member of the editorial board of Briefings in Bioinformatics, passed away on 14 May 2012. Professor Dr Jack A.M. Leunissen was one of the pioneers of bioinformatics in the Netherlands, in Europe and around the world. Together with senior members of the European Molecular Biology Network (EMBnet), Jack worked with Henry Stewart Publications to launch this journal in 2000, aiming to publish review articles in bioinformatics to benefit the ever-growing community of bioinformatics researchers. He served as a member of the editorial board for >10 years, devoting much of his time to reviewing manuscripts and providing constructive feedback. Born on 1 August 1954 and educated as a biochemist in the 1980s, Jack showed an interest in bioinformatics early in his scientific career. He created the Biocomputing Environment at the University of Nijmegen in 1982, and his PhD thesis, ‘Computer Applications in Protein and Nucleic Acid Sequence Analysis’ in 1989 was one of the earliest in the biocomputing community. During his PhD studies, Jack started the biocomputing section of the Dutch National academic facility for computer-assisted organic synthesis and modelling and worked there for >10 years. In that period, Jack was also strongly involved in the establishment of EMBnet. He was manager of his country’s node and served as Chairman of the Executive Board of EMBnet from 1999 to 2003. In 2000, he was appointed as senior lecturer in bioinformatics at the Centre for Molecular and Biomolecular Informatics at Nijmegen University. At the end of 2002, he accepted the position of Chair in Bioinformatics at the Department of Plant Sciences of the Wageningen University and Research Center. At the same time, he was involved in the newly formed Netherlands Bioinformatics Centre as project leader, member of the National Advisory Committee and member of the Management Team. Jack had a broad interest in bioinformatics related topics, which he was able to pass on to his PhD and MSc students, working on diverse subjects such as text mining, protein orthology, comparative anatomy, web services and Bayesian networks. His curiosity put him in touch with experts from various related disciplines like computer science, mathematics, statistics and linguistics. Even during the tenure of his professorship, he enjoyed exploring new programming languages and technologies to evaluate their usefulness for bioinformatics. Despite his illness, he continued to be actively involved in the work of his students until the end, including reviewing the article ‘Understanding and Identification of Amino Acid Repeats’ published in this issue by his students. It is hard to overstate the contribution that Jack made to bioinformatics education and training, especially to end users coming from biological backgrounds. From the mid 80s, he taught on numerous courses, workshops and conferences within and outside Europe. Together with other colleagues, he taught on the Bioinformatics summer school at the International Center for Genetic Engineering and Biotechnology in Trieste almost every year from 1993. He was also invited to teach several courses in Peking University, where the Chinese EMBnet node is located. Those he taught will never forget his enthusiasm and inspirational style in the class room. In May 2012, he received a prestigious award from the Dutch industry platform for his activities towards making education and training software and databases more accessible for everybody. Jack, we miss you greatly.

Genome browser provides a graphical interface for users to browse, search, retrieve and analyze genomic sequence and annotation data. Web-based genome browsers can be classified into general genome browsers with multiple species and species-specific genome browsers. In this review, we attempt to give an overview for the main functions and features of web-based genome browsers, covering data visualization, retrieval, analysis and customization. To give a brief introduction to the multiple-species genome browser, we describe the user interface and main functions of the Ensembl and UCSC genome browsers using the human alpha-globin gene cluster as an example. We further use the MSU and the Rice-Map genome browsers to show some special features of species-specific genome browser, taking a rice transcription factor gene OsSPL14 as an example.

BACKGROUND: With the rapid growth of genome sequencing projects, genome browser is becoming indispensable, not only as a visualization system but also as an interactive platform to support open data access and collaborative work. Thus a customizable genome browser framework with rich functions and flexible configuration is needed to facilitate various genome research projects. RESULTS: Based on next-generation web technologies, we have developed a general-purpose genome browser framework ABrowse which provides interactive browsing experience, open data access and collaborative work support. By supporting Google-map-like smooth navigation, ABrowse offers end users highly interactive browsing experience. To facilitate further data analysis, multiple data access approaches are supported for external platforms to retrieve data from ABrowse. To promote collaborative work, an online user-space is provided for end users to create, store and share comments, annotations and landmarks. For data providers, ABrowse is highly customizable and configurable. The framework provides a set of utilities to import annotation data conveniently. To build ABrowse on existing annotation databases, data providers could specify SQL statements according to database schema. And customized pages for detailed information display of annotation entries could be easily plugged in. For developers, new drawing strategies could be integrated into ABrowse for new types of annotation data. In addition, standard web service is provided for data retrieval remotely, providing underlying machine-oriented programming interface for open data access. CONCLUSIONS: ABrowse framework is valuable for end users, data providers and developers by providing rich user functions and flexible customization approaches. The source code is published under GNU Lesser General Public License v3.0 and is accessible at http://www.abrowse.org/. To demonstrate all the features of ABrowse, a live demo for Arabidopsis thaliana genome has been built at http://arabidopsis.cbi.edu.cn/.

SUMMARY: NTAP is designed to analyze ChIP-chip data generated by the NimbleGen tiling array platform and to accomplish various pattern recognition tasks that are useful especially for epigenetic studies. The modular design of NTAP makes the data processing highly customizable. Users can either use NTAP to perform the full process of NimbleGen tiling array data analysis, or choose post-processing modules in NTAP to analyze pre-processed epigenetic data generated by other platforms. The output of NTAP can be saved in standard GFF format files and visualized in GBrowse. AVAILABILITY AND IMPLEMENTATION: The source code of NTAP is freely available at http://ntap.cbi.pku.edu.cn/. It is implemented in Perl and R and can be used on Linux, Mac and Windows platforms.

BACKGROUND: Genome-wide duplication is ubiquitous during diversification of the angiosperms, and gene duplication is one of the most important mechanisms for evolutionary novelties. As an indicator of functional evolution, the divergence of expression patterns following duplication events has drawn great attention in recent years. Using large-scale whole-genome microarray data, we systematically analyzed expression divergence patterns of rice genes from block, tandem and dispersed duplications. RESULTS: We found a significant difference in expression divergence patterns for the three types of duplicated gene pairs. Expression correlation is significantly higher for gene pairs from block and tandem duplications than those from dispersed duplications. Furthermore, a significant correlation was observed between the expression divergence and the synonymous substitution rate which is an approximate proxy of divergence time. Thus, both duplication types and divergence time influence the difference in expression divergence. Using a linear model, we investigated the influence of these two variables and found that the difference in expression divergence between block and dispersed duplicates is attributed largely to their different divergence time. In addition, the difference in expression divergence between tandem and the other two types of duplicates is attributed to both divergence time and duplication type. CONCLUSION: Consistent with previous studies on Arabidopsis, our results revealed a significant difference in expression divergence between the types of duplicated genes and a significant correlation between expression divergence and synonymous substitution rate. We found that the attribution of duplication mode to the expression divergence implies a different evolutionary course of duplicated genes.

UNLABELLED: We have developed a package named Application for Bioinformatics Computing Grid (ABCGrid). ABCGrid was designed for biology laboratories to use heterogeneous computing resources and access bioinformatics applications from one master node. ABCGrid is very easy to install and maintain at the premise of robustness and high performance. We implement a mechanism to install and update all applications and databases in worker nodes automatically to reduce the workload of manual maintenance. We use a backup task method and self-adaptive job dispatch approach to improve performance. Currently, ABCGrid integrates NCBI_BLAST, Hmmpfam and CE, running on a number of computing platforms including UNIX/Linux, Windows and Mac OS X. AVAILABILITY: The source code, executables and documents can be downloaded from http://abcgrid.cbi.pku.edu.cn

The database of poplar transcription factors (DPTF) is a plant transcription factor (TF) database containing 2576 putative poplar TFs distributed in 64 families. These TFs were identified from both computational prediction and manual curation. We have provided extensive annotations including sequence features, functional domains, GO assignment and expression evidence for all TFs. In addition, DPTF contains cross-links to the Arabidopsis and rice transcription factor databases making it a unique resource for genome-scale comparative studies of transcriptional regulation in model plants. Availiability: DPTF is available at http://dptf.cbi.pku.edu.cn.

SUMMARY: DRTF contains 2025 putative transcription factors (TFs) in Oryza sativa L. ssp. indica and 2384 in ssp. japonica, distributed in 63 families, identified by computational prediction and manual curation. It includes detailed annotations of each TF including sequence features, functional domains, Gene Ontology assignment, chromosomal localization, EST and microarray expression information, as well as multiple sequence alignment of the DNA-binding domains for each TF family. The database can be browsed and searched with a user-friendly web interface. AVAILABILITY: DRTF is available at http://drtf.cbi.pku.edu.cn

BACKGROUND: The identification of chromosomal homology will shed light on such mysteries of genome evolution as DNA duplication, rearrangement and loss. Several approaches have been developed to detect chromosomal homology based on gene synteny or colinearity. However, the previously reported implementations lack statistical inferences which are essential to reveal actual homologies. RESULTS: In this study, we present a statistical approach to detect homologous chromosomal segments based on gene colinearity. We implement this approach in a software package ColinearScan to detect putative colinear regions using a dynamic programming algorithm. Statistical models are proposed to estimate proper parameter values and evaluate the significance of putative homologous regions. Statistical inference, high computational efficiency and flexibility of input data type are three key features of our approach. CONCLUSION: We apply ColinearScan to the Arabidopsis and rice genomes to detect duplicated regions within each species and homologous fragments between these two species. We find many more homologous chromosomal segments in the rice genome than previously reported. We also find many small colinear segments between rice and Arabidopsis genomes.

UNLABELLED: We have probably developed the most comprehensive database of Arabidopsis transcription factors (DATF). The DATF contains known and predicted Arabidopsis transcription factors (1827 genes in 56 families) with the unique information of 1177 cloned sequences and many other features including 3D structure templates, EST expression information, transcription factor binding sites and nuclear location signals. AVAILABILITY: DATF is freely available at http://datf.cbi.pku.edu.cn

MOTIVATION: In order to accelerate the finishing phase of genome assembly, especially for the whole genome shotgun approach of prokaryotic species, we have developed a software package designated prokaryotic genome assembly assistant system (PGAAS). The approach upon which PGAAS is based is to confirm the order of contigs and fill gaps between contigs through peptide links obtained by searching each contig end with BLASTX against protein databases. RESULTS: We used the contig dataset of the cyanobacterium Synechococcus sp. strain PCC7002 (PCC7002), which was sequenced with six-fold coverage and assembled using the Phrap package. The subject database is the protein database of the cyanobacterium, Synechocystis sp. strain PCC6803 (PCC6803). We found more than 100 non-redundant peptide segments which can link at least 2 contigs. We tested one pair of linked contigs by sequencing and obtained satisfactory result. PGAAS provides a graphic user interface to show the bridge peptides and pier contigs. We integrated Primer3 into our package to design PCR primers at the adjacent ends of the pier contigs. AVAILABILITY: We tested PGAAS on a Linux (Redhat 6.2) PC machine. It is developed with free software (MySQL, PHP and Apache). The whole package is distributed freely and can be downloaded as UNIX compress file: ftp://ftp.cbi.pku.edu.cn/pub/software/unix/pgaas1.0.tar.gz. The package is being continually updated.