Website review: how to get the best from fission yeast genome data

Researchers are increasingly depending on various centralized resources to access the vast amount of information reported in the literature and generated by systematic sequencing and functional genomics projects. Biological databases have become everyday working tools for many researchers. This dependency goes both ways in that the databases require continuous feedback from the research community to maintain accurate, reliable, and upto- date information. The fission yeast Schizosaccharomyces pombe has recently been sequenced, setting the stage for the post-genome era of this popular model organism. Here, we provide an overview of relevant databases available, or being developed, together with a compilation of Internet resources containing useful information and tools for fission yeast.     

Atlas of Genetics and Cytogenetics in Oncology and Haematology, updated

The 'Atlas of Genetics and Cytogenetics in Oncology and Haematology' (http://www.infobiogen.fr/services/chromcancer) is an Internet database aimed at genes involved in cancer, cytogenetics and clinical entities in cancer, and cancer-prone diseases. It presents information in concise and updated reviews (cards) or longer texts (deep insights), a (new) case report section, a huge portal towards genetics and/or cancer databases, and teaching items in genetics for students in medicine and the sciences. This database is made for and by clinicians and researchers in the above-mentioned fields, who are encouraged to contribute. It deals with cancer research, genomics and cytogenomics. It is at the crossroads of research, post-university teaching and telemedicine. The Atlas is available at no cost.     

The Path to Enlightenment： Making Sense of Genomic and Proteomic Information

Whereas genomics describes the study of genome, mainly represented by its gene expression on the DNA or RNA level, the term proteomics denotes the study of the proteome, which is the protein complement encoded by the genome. In recent years, the number of proteomic experiments increased tremendously. While all fields of proteomics have made major technological advances, the biggest step was seen in bioinformatics. Biological information management relies on sequence and structure databases and powerful software tools to translate experimental results into meaningful biological hypotheses and answers. In this resource article, I provide a collection of databases and software available on the Internet that are useful to interpret genomic and proteomic data. The article is a toolbox for researchers who have genomic or proteomic datasets and need to put their findings into a biological context.     

The protein kinase resource and other bioinformation resources

The Internet, especially the World Wide Web has transformed how today's researchers communicate, share information, and analyze their data. Unfortunately, the vast number of online databases, information resources and analytical tools, some of them masked by unfamiliar titles and Internet addresses, has hindered their universal and effective use by the research community. To overcome these hurdles, subject- and function-specific compendiums are now available which organize information and online tolls in a manner familiar to the biological researcher. The Protein Kinase Resource and the CMS Molecular Biology Resource are two excellent examples of web compendia.     

Workflow management systems for gene sequence analysis and evolutionary studies – A Review

Post ‘omic’ era has resulted in the development of many primary, secondary and derived databases. Many analytical and visualization bioinformatics tools have been developed to manage and analyze the data available through large sequencing projects. Availability of heterogeneous databases and tools make it difficult for researchers to access information from varied sources and run different bioinformatics tools to get desired analysis done. Building integrated bioinformatics platforms is one of the most challenging tasks that bioinformatics community is facing. Integration of various databases, tools and algorithm is a challenging problem to deal with. This article describes the bioinformatics analysis workflow management systems that are developed in the area of gene sequence analysis and phylogeny. This article will be useful for biotechnologists, molecular biologists, computer scientists and statisticians engaged in computational biology and bioinformatics research.     

Biotechnology,Big Data and Artificial Intelligence

Developments in biotechnology are increasingly dependent on the extensive use of big data, generated by modern high‐throughput instrumentation technologies, and stored in thousands of databases, public and private. Future developments in this area depend, critically, on the ability of biotechnology researchers to master the skills required to effectively integrate their own contributions with the large amounts of information available in these databases. This article offers a perspective of the relations that exist between the fields of big data and biotechnology, including the related technologies of artificial intelligence and machine learning and describes how data integration, data exploitation, and process optimization correspond to three essential steps in any future biotechnology project. The article also lists a number of application areas where the ability to use big data will become a key factor, including drug discovery, drug recycling, drug safety, functional and structural genomics, proteomics, pharmacogenetics, and pharmacogenomics, among others.     

Using the two-hybrid screen in the classroom laboratory

The National Science Foundation and others have made compelling arguments that research be incorporated into the learning of undergraduates. In response to these arguments, a two-hybrid research project was incorporated into a molecular biology course that contained both a lecture section and a laboratory section. The course was designed around specific goals for educational outcomes, including introducing research to a wide range of students, teaching students experimental design and data analysis, and enhancing understanding of course material. Additional goals included teaching students to search genomic databases, to access scientific articles, and to write a paper in scientific format. Graded events tested these goals, and a student evaluation indicated student perception of the project. According to our analysis of the data, the yeast two-hybrid screen was a success: several novel clones were identified; students met expectations on graded lab reports, the poster session, and the final paper; and evaluations indicated that students had achieved the outlined goals. Students indicated on the evaluations that the research project increased their interest in research and greatly improved understanding of the course material. Finally, several students in the course intend to submit the findings of the research project to an undergraduate research journal.     

Evolving strategies for the incorporation of bioinformatics within the undergraduate cell biology curriculum

Recent advances in genomics and structural biology have resulted in an unprecedented increase in biological data available from Internet-accessible databases. In order to help students effectively use this vast repository of information, undergraduate biology students at Drake University were introduced to bioinformatics software and databases in three courses, beginning with an introductory course in cell biology. The exercises and projects that were used to help students develop literacy in bioinformatics are described. In a recently offered course in bioinformatics, students developed their own simple sequence analysis tool using the Perl programming language. These experiences are described from the point of view of the instructor as well as the students. A preliminary assessment has been made of the degree to which students had developed a working knowledge of bioinformatics concepts and methods. Finally, some conclusions have been drawn from these courses that may be helpful to instructors wishing to introduce bioinformatics within the undergraduate biology curriculum.     

Towards a cyberinfrastructure for the biological sciences: progress, visions and challenges

Biology is an information-driven science. Large-scale data sets from genomics, physiology, population genetics and imaging are driving research at a dizzying rate. Simultaneously, interdisciplinary collaborations among experimental biologists, theorists, statisticians and computer scientists have become the key to making effective use of these data sets. However, too many biologists have trouble accessing and using these electronic data sets and tools effectively. A 'cyberinfrastructure' is a combination of databases, network protocols and computational services that brings people, information and computational tools together to perform science in this information-driven world. This article reviews the components of a biological cyberinfrastructure, discusses current and pending implementations, and notes the many challenges that lie ahead.     

基因转录调控相关数据库集成系统及其应用

通过互联网访问的有关基因转录调控的数据库集成系统及其应用 ,包括调控区 (3’和 5’调控区、内显子和外显子调控区等 )、调控单元 (启动子 ,增强子 ,沉默子等 )和转录因子结合位点相关数据库及其数据库系统的性质、组成和功能。也介绍了这些数据库和系统的查询和搜索方法以及相关开发的程序工具。这些生物信息学资源对于从事生物信息学、分子生物学、遗传工程、基因功能、生物技术、代谢工程、药物设计、病理学和药理学研究的机构及人员在教学研究方面具一定的参考价值和帮助。     

The NIDDK Information Network: A Community Portal for Finding Data,Materials, and Tools for Researchers Studying Diabetes,Digestive, and Kidney Diseases

The NIDDK Information Network (dkNET; http://dknet.org) was launched to serve the needs of basic and clinical investigators in metabolic, digestive and kidney disease by facilitating access to research resources that advance the mission of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). By research resources, we mean the multitude of data, software tools, materials, services, projects and organizations available to researchers in the public domain. Most of these are accessed via web-accessible databases or web portals, each developed, designed and maintained by numerous different projects, organizations and individuals. While many of the large government funded databases, maintained by agencies such as European Bioinformatics Institute and the National Center for Biotechnology Information, are well known to researchers, many more that have been developed by and for the biomedical research community are unknown or underutilized. At least part of the problem is the nature of dynamic databases, which are considered part of the “hidden” web, that is, content that is not easily accessed by search engines. dkNET was created specifically to address the challenge of connecting researchers to research resources via these types of community databases and web portals. dkNET functions as a “search engine for data”, searching across millions of database records contained in hundreds of biomedical databases developed and maintained by independent projects around the world. A primary focus of dkNET are centers and projects specifically created to provide high quality data and resources to NIDDK researchers. Through the novel data ingest process used in dkNET, additional data sources can easily be incorporated, allowing it to scale with the growth of digital data and the needs of the dkNET community. Here, we provide an overview of the dkNET portal and its functions. We show how dkNET can be used to address a variety of use cases that involve searching for research resources.     

Cancer and the web

The applications of functional genomics, proteomics and informatics to cancer research have yielded a tremendous amount of information, which is growing all the time. Much of this information is available publicly on the Internet and ranges from general information about different cancers from a patient or clinical viewpoint, through to databases suitable for cancer researchers of all backgrounds, to very specific sites dedicated to individual genes or molecules. A simple search for 'cancer' from a typical Web browser search engine yields more than half a million hits; an even more specific search for 'leukaemia' (>40 000 hits) or 'p53' (>5700 hits) yields far too many hits to allow one to identify particular sites of interest. This review aims to provide a brief guide to some of the resources and databases that can be used as springboards to home in rapidly on information relevant to many fields of cancer research. As such, this article will not focus on a single website but hopes to illustrate some of the ways that postgenomic biology is revolutionizing cancer research. It will cover genomics and proteomics approaches that have been applied to studying global expression patterns in cancers, in addition to providing links ranging from general information about cancer to specific cancer gene mutation databases.     

Next‐generation field courses: Integrating Open Science and online learning

As Open Science practices become more commonplace, there is a need for the next generation of scientists to be well versed in these aspects of scientific research. Yet, many training opportunities for early career researchers (ECRs) could better emphasize or integrate Open Science elements. Field courses provide opportunities for ECRs to apply theoretical knowledge, practice new methodological approaches, and gain an appreciation for the challenges of real‐life research, and could provide an excellent platform for integrating training in Open Science practices. Our recent experience, as primarily ECRs engaged in a field course interrupted by COVID‐19, led us to reflect on the potential to enhance learning outcomes in field courses by integrating Open Science practices and online learning components. Specifically, we highlight the opportunity for field courses to align teaching activities with the recent developments and trends in how we conduct research, including training in: publishing registered reports, collecting data using standardized methods, adopting high‐quality data documentation, managing data through reproducible workflows, and sharing and publishing data through appropriate channels. We also discuss how field courses can use online tools to optimize time in the field, develop open access resources, and cultivate collaborations. By integrating these elements, we suggest that the next generation of field courses will offer excellent arenas for participants to adopt Open Science practices.     

Cell biology, chemogenomics and chemoproteomics

The scientific techniques used in molecular biological research and drug discovery have changed dramatically over the past 10 years due to the influence of genomics, proteomics and bioinformatics. Furthermore, genomics and functional genomics are now merging into a new scientific approach called chemogenomics. Advancements in the study of molecular cell biology are dependent upon "omics" researchers realizing the importance of and using the experimental tools currently available to cell biologists. For example, novel microscopic techniques utilizing advanced computer imaging allow for the examination of live specimens in a fourth dimension, viz., time. Yet, molecular biologists have not taken full advantage of these and other traditional and novel cell biology techniques for the further advancement of genomic and proteomic-oriented research. The application of traditional and novel cellular biological techniques will enhance the science of genomics. The authors hypothesize that a stronger interdisciplinary approach must be taken between cell biology (and its closely related fields) and genomics, proteomics and bio-chemoinformatics. Since there is a lot of confusion regarding many of the "omics" definitions, this article also clarifies some of the basic terminology used in genomics, and related fields. It also reviews the current status and future potential of chemogenomics and its relationship to cell biology. The authors also discuss and expand upon the differences between chemogenomics and the relatively new term--chemoproteomics. We conclude that the advances in cell biology methods and approaches and their adoption by "omics" researchers will allow scientists to maximize our knowledge about life.     

FisOmics: A portal of fish genomic resources

An online portal, accessible at URL: http://mail.nbfgr.res.in/FisOmics/, was developed that features different genomic databases and tools. The portal, named as FisOmics, acts as a platform for sharing fish genomic sequences and related information in addition to facilitating the access of high-performance computational resources for genome and proteome data analyses. It provides the ability for quarrying, analysing and visualizing genomic sequences and related information. The featured databases in FisOmics are in the World Wide Web domain already. The aim to develop portal was to provide a nodal point to access the featured databases and work conveniently. Presently, FisOmics includes databases on barcode sequences, microsatellite markers, mitogenome sequences, hypoxia-responsive genes and karyology of fishes. Besides, it has a link to other molecular resources and reports on the on-going activities and research achievements.     

Educating health-care professionals about genetics and genomics

To biomedical researchers, this is the 'genome era'. Advances in genetics and genomics such as the sequence of the human genome, the human haplotype map, open access databases, cheaper genotyping and chemical genomics have already transformed basic and translational biomedical research. However, for most clinicians, the genome era has not yet arrived. For genomics to have an effect on clinical practice that is comparable to its impact on research will require advances in the genomic literacy of health-care providers. Here we describe the knowledge, skills and attitudes that genomic medicine will require, and approaches to integrate them into the health-care community.     

An inexpensive gel electrophoresis-based polymerase chain reaction method for quantifying mRNA levels

In order to engage their students in a core methodology of the new genomics era, an ever-increasing number of faculty at primarily undergraduate institutions are gaining access to microarray technology. Their students are conducting successful microarray experiments designed to address a variety of interesting questions. A next step in these teaching and research laboratory projects is often validation of the microarray data for individual selected genes. In the research community, this usually involves the use of real-time polymerase chain reaction (PCR), a technology that requires instrumentation and reagents that are prohibitively expensive for most undergraduate institutions. The results of a survey of faculty teaching undergraduates in classroom and research settings indicate a clear need for an alternative approach. We sought to develop an inexpensive and student-friendly gel electrophoresis-based PCR method for quantifying messenger RNA (mRNA) levels using undergraduate researchers as models for students in teaching and research laboratories. We compared the results for three selected genes measured by microarray analysis, real-time PCR, and the gel electrophoresis-based method. The data support the use of the gel electrophoresis-based method as an inexpensive, convenient, yet reliable alternative for quantifying mRNA levels in undergraduate laboratories.