Bioinformatics

“ Endeavors to achieve uniformity significantly enhance the efficiency of data curation and exchange. Such reform should eventually diffuse throughout the scientific community and be reflected in the literature.
New methodologies allow scientific data to grow at an exponential pace, creating a steady demand for reliable, consistent, and accurate databases. As bioinformatics resources continue to grow, so will the role of the biocurator in their development. The expansion of bioinformatics and its applications paints a promising future for the biocurator. ”

“ Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. ”

“ Thus, a bioinformatics engineer must have strengths in computational and statistical sciences and must have general competency in biomedical sciences. Bioinformatics engineers design the infrastructure and systems for bioinformatics analysis, integrating software, databases, and hardware. This can involve the choice or design of hardware and software for the storage and management of diverse and distributed data, selection or development of tools and algorithms for integration and analysis of these data, and design of suitable user interfaces. ”

“ The skill sets required for success in the field of bioinformatics are considered by several authors: Altman [2] defines five broad areas of competency and lists key technologies; Ranganathan [3] presents highlights from the Workshops on Education in Bioinformatics, discussing challenges and possible solutions; Yale's interdepartmental PhD program in computational biology and bioinformatics is described in [4] , which lists the general areas of knowledge of bioinformatics; in a related article, a graduate of Yale's PhD program reflects on the skills needed by a bioinformatician [5] ”

“ As the practices of genomic and personalized medicine increase, we anticipate a growing need for training clinicians in the use of bioinformatics data and tools. Other bioinformatics users include legal professionals and K-12 biology teachers.
The authors use personas to refine their understanding of different types of computational biologists and the competencies that they require to perform their roles. Designers of commercial products frequently create “personas”—archetypes based on data and research on the users for whom a product is being designed—to facilitate the design process. ”

“ The biocurator's role is dynamic and evolves in parallel with developments in bioinformatics, bridging the gap between knowledge and its accessibility. Regardless of the source and subject of the data, the biocurator accumulates disparate, but relevant data into one centralized location where it is made more accessible to researchers. The organized and analyzed data are thus made available for retrieval, analysis, and download by the end-user in an enhanced format, providing an added dimension of utility that would not otherwise be present. ”

“ As the discipline of bioinformatics and computational biology expands and matures, it is important to characterize the elements that contribute to the success of professionals in this field. These individuals work in a wide variety of settings, including bioinformatics core facilities, biological and medical research laboratories, software development organizations, pharmaceutical and instrument development companies, and institutions that provide education, service, and training. ”

“ The critical and complex nature of bioinformatics software and the growing volume of associated data require the development of reliable and maintainable systems in an environment where requirements can be complex, vague, and volatile, and budgets and schedules are often tight. In addition to strong scientific foundations and technical skills the bioinformatics engineer needs to bring to bear engineering competencies such as systems design and project management to ensure the quality, viability, and sustainability of the software systems developed. ”

“ How well do the new graduates from these educational programs fit the jobs available to them? How many areas should a bioinformatics graduate be an expert in? Apart from a deep understanding of algorithms, programming, and life sciences, solving problems in genomics, proteomics, and/or medical informatics appears to be the current requirement. With the blurring boundaries between bioinformatics and new areas of endeavor such as forensics and biodiversity/ecoinformatics, where should we, as educators, draw the line? ”

“ Several approaches to providing bioinformatics training for biologists are described in the literature. Tan et al. [9] report on workshops conducted to identify a minimum skill set for biologists to be able to address the informatics challenges of the “-omics” era. ”

“ The bioinformatics literature provides valuable perspectives on bioinformatics education by defining skill sets needed by bioinformaticians, presenting approaches for providing informatics training to biologists, and discussing the roles of bioinformatics core facilities in training and education. ”

“ The columns of Table 2 indicate core competencies for three different types of individuals that have a need for bioinformatics training. (The three categories of bioinformatics training are not meant to capture all possible types of bioinformatics training needed but to describe three common categories.) Bioinformatics users access data resources to perform job duties in specific application domains. Bench-based researchers, both in academia and in industry, provide the classic example of a bioinformatics user, but this group is broadening in scope. ”

“ To be a fully integrated member of a research team, a bioinformatician must possess detailed knowledge of molecular biology, genomics, genetics, cell biology, biochemistry, and evolutionary theory. Furthermore, it is necessary to understand related technologies, including next generation sequencing and proteomics/mass spectrometry. It is also desirable for a bioinformatician to have modeling experience or background in one or more specialized domains, such as systems biology, inflammation, immunology, cell signaling, or physiology. ”

“ With respect to domain-specific skills, directors need people well versed in biology, bioinformatics, statistics, and programming, essentially needing people with technical experience in both biological sciences and computational methods. New hires often lack experience in the analysis of real biological data. ”

“ Education in bioinformatics has undergone a sea change, from informal workshops and training courses to structured certificate, diploma, and degree programs—spanning casual self-enriching courses all the way to doctorate programs. The evolution of curriculum, instructional methodologies, and initiatives supporting the dissemination of bioinformatics is presented here. ”

“ While it is important for a bioinformatician to have a suite of computational, mathematical, and statistical skills, this alone is insufficient. Throughout their careers, bioinformaticians usually contribute to a variety of scientific projects, such as variant detection in human exome resequencing; human genetic diversity ”

“ Additionally, a bioinformatician should be able to incorporate components from open source software repositories into a software system. The ability to effectively utilize distributed and high-performance computing to analyze large data sets is essential, as is knowledge of networking technology and internet protocols. A bioinformatician should be able to utilize web authoring tools, web-based user interface implementation technologies, and version control and build tools (e.g., subversion, Ant, and Netbeans) . ”

“ An ability to use current techniques, skills, and tools necessary for computing practice,” one should consider including adequate time for familiarization with the command line, data management practice, and statistical analysis tools.
File:Pcbi.1003496.g002A persona based on a typical “bioinformatics user.” QA: Quality Assurance, GUI: Graphical User Interface.Image credit: Jenny Cham, Mary Todd Bergman, and Cath Brooksbank, EMBL-EBI. Bioinformatics scientists are biologists who employ computational methods in order to advance the scientific understanding of living systems. ”

“ Not surprisingly, general skills needed at the PhD level include those skills necessary at the master level, as well as communications skills, management skills, and the ability to help others. Skills most frequently found lacking in individuals with PhDs include communications skills, ability to synthesize information, ability to complete projects, and leadership skills. The domain-specific skills were similar to those needed at the master level, but emphasized more prior experience in bioinformatics, data analysis, and statistics. ”

“ In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions—that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. ”

“ Our computational analysis has important implications for understanding disease mechanisms and how environmental factors, such as drugs, influence human health. Finally, we provide all gene-disease networks in a user-friendly way through DisGeNET [28] , a Cytoscape plugin and as SQLite database for direct computational access to aid future research of disease-related processes that will also benefit drug discovery and development. ”

“ These measures are in turn normalized to derive an overall measure across all networks, which is used to rank all candidate genes. For each candidate-disease gene pair, only the most informative network will contribute to the final gene-disease relationship. In this way, we can automatically minimize errors from unreliable data sources. We performed large scale cross-validation analysis on 110 disease families from the OMIM database using three data sources, based on protein interactions, gene expressions and pathway information. ”

“ Most importantly, our results suggest that the reciprocal search will work, where we will be able to identify animal models of human disease (or disease pathways) where the human gene is not yet known. In order to implement this, we intend to annotate the remainder of OMIM using the EQ method on OMIM phenotype synopses, and supplement the database with other disease data, to provide the necessary phenotypes for comparison. Because a mutated gene in an animal model is more readily available or identifiable, our method may hasten the identification of the genetic basis of human diseases. ”

“ Our protein interaction network was constructed from the STRING database, which includes both physical and functional interactions integrated from numerous sources, including experimental repositories, computational prediction methods and public text collections. Eliminating self-interactions, this network consists of 1,032,872 interactions between 14,532 proteins of human genome, with their normalized interaction weights in the STRING database. ”

“ The known disease genes in the OMIM database were used to determine parameters φ and η, as well as to assess the performance of our algorithm. For a known disease gene in a candidate gene set of size N, if its s-rank calculated by our algorithm is r, then its r-ratio defined as r/N, could reflect how strong this gene is predicted as a disease gene. We determined parameters φ and η as those minimized the average r-ratios of the known OMIM disease genes. ”

“ A variety of technologies exist to measure the levels of many such activities. Over the years, a vast amount of data from different sources has been accumulated and stored in a huge number of biological databases, many of which are publicly available. For a particular disease, such as breast cancer, tissue gene expression data might exist in some databases. Known disease genes and their interacting parters may have been recorded in protein-protein interaction (PPI) databases. Researchers may have also collected and constructed disease pathways based on previous studies. ”

“ The literature-derived human gene-disease network (LHGDN) is a text mining derived database with focus on extracting and classifying gene-disease associations with respect to several biomolecular conditions. It uses a machine learning based algorithm to extract semantic gene-disease relations from a textual source of interest. ”

“ OMIM has become a highly popular source in medical genetics [6] . It traditionally focused on mendelian diseases and later started to include complex diseases as well. In the last years, other databases have been built, among them the Pharmacogenomics Knowledge Base (PHARMGKB) specialized on the knowledge about genes that are involved in modulating drug response [7] or the Comparative Toxicogenomics Database (CTD) focused on the effect of environmental chemicals on human disease [8] . Each of the databases focuses on different aspects of phenotype-genotype relationships. ”