SinicView: A visualization environment for comparisons of multiple nucleotide sequence alignment tools

Background  

Deluged by the rate and complexity of completed genomic sequences, the need to align longer sequences becomes more urgent, and many more tools have thus been developed. In the initial stage of genomic sequence analysis, a biologist is usually faced with the questions of how to choose the best tool to align sequences of interest and how to analyze and visualize the alignment results, and then with the question of whether poorly aligned regions produced by the tool are indeed not homologous or are just results due to inappropriate alignment tools or scoring systems used. Although several systematic evaluations of multiple sequence alignment (MSA) programs have been proposed, they may not provide a standard-bearer for most biologists because those poorly aligned regions in these evaluations are never discussed. Thus, a tool that allows cross comparison of the alignment results obtained by different tools simultaneously could help a biologist evaluate their correctness and accuracy.     

Biological systems modeling and analysis: a biomolecular technique of the twenty-first century.

It is proposed that computational systems biology should be considered a biomolecular technique of the twenty-first century, because it complements experimental biology and bioinformatics in unique ways that will eventually lead to insights and a depth of understanding not achievable without systems approaches. This article begins with a summary of traditional and novel modeling techniques. In the second part, it proposes concept map modeling as a useful link between experimental biology and biological systems modeling and analysis. Concept map modeling requires the collaboration between biologist and modeler. The biologist designs a regulated connectivity diagram of processes comprising a biological system and also provides semi-quantitative information on stimuli and measured or expected responses of the system. The modeler converts this information through methods of forward and inverse modeling into a mathematical construct that can be used for simulations and to generate and test new hypotheses. The biologist and the modeler collaboratively interpret the results and devise improved concept maps. The third part of the article describes software, BST-Box, supporting the various modeling activities.     

Application of a systems approach to study developmental gene regulation

All cells in a multicellular organism contain the same genome, yet different cell types express different sets of genes. Recent advances in high throughput genomic technologies have opened up new opportunities to understand the gene regulatory network in diverse cell types in a genome-wide manner. Here, I discuss recent advances in experimental and computational approaches for the study of gene regulation in embryonic development from a systems perspective. This review is written for computational biologists who have an interest in studying developmental gene regulation through integrative analysis of gene expression, chromatin landscape, and signaling pathways. I highlight the utility of publicly available data and tools, as well as some common analysis approaches.     

From correlation to causation: The new frontier of transgenerational epigenetic inheritance

While heredity is predominantly controlled by what deoxyribonucleic acid (DNA) sequences are passed from parents to their offspring, a small but growing number of traits have been shown to be regulated in part by the non-genetic inheritance of information. Transgenerational epigenetic inheritance is defined as heritable information passed from parents to their offspring without changing the DNA sequence. Work of the past seven decades has transitioned what was previously viewed as rare phenomenology, into well-established paradigms by which numerous traits can be modulated. For the most part, studies in model organisms have correlated transgenerational epigenetic inheritance phenotypes with changes in epigenetic modifications. The next steps for this field will entail transitioning from correlative studies to causal ones. Here, we delineate the major molecules that have been implicated in transgenerational epigenetic inheritance in both mammalian and non-mammalian models, speculate on additional molecules that could be involved, and highlight some of the tools which might help transition this field from correlation to causation.     

Reflections on the scope and the future of metabolic engineering and its connections to functional genomics and drug discovery

Concepts, experience, and tools from metabolic engineering are immediately applicable to the challenge of understanding how the genome influences phenotype. However, new experimental approaches and mathematical and computational resources are needed to maximize the contributions of metabolic engineering to general questions in functional genomics. Among the priorities are systems for studying physiology on a microscale, theoretical tools for understanding biological control systems, and metabolic simulators "in silico" which provide reasonable predictions of stimulus-response relationships at engineering and medical resolution, with incomplete information on cellular mechanisms and their parameters. Approaching cells as complex systems, already a well-established principle in metabolic engineering, is essential to surmount stagnation in the rate of pharmaceutical discovery which is still based on a naive single-target paradigm.     

MITOMAP: an update on the status of the human mitochondrial genome database.

We have continued to develop MITOMAP, a comprehensive database for the human mitochondrial DNA (mtDNA). MITOMAP uses the mtDNA sequence as the unifying element for bringing together information on mitochondrial genome structure and function, pathogenic mutations and their clinical characteristics, population associated variation and gene-gene interactions. As increasingly larger regions of the human genome are sequenced and characterized, the need for integrating such information will grow. Consequently, MITOMAP not only provides a valuable reference for the mitochondrial biologist, it will also provide a model for the development of comprehensive, multi-media information storage and retrieval systems for other components of the human genome. This paper is an update of the changes which have occurred to MITOMAP over the past year.     

The Candida Genome Database: facilitating research on Candida albicans molecular biology

The Candida Genome Database (CGD; http://www.candidagenome.org) is a resource for information about the Candida albicans genomic sequence and the molecular biology of its encoded gene products. CGD collects and organizes data from the biological literature concerning C. albicans, and provides tools for viewing, searching, analysing, and downloading these data. CGD also serves as an organizing centre for the C. albicans research community, providing a gene-name registry, contact information, and research community news. This article describes the information contained in CGD and how to access it, either from the perspective of a bench scientist interested in the function of one or a few genes, or from the perspective of a biologist or bioinformatician interpreting large-scale functional genomic datasets.     

DraGnET: Software for storing,managing and analyzing annotated draft genome sequence data

Background  

New "next generation" DNA sequencing technologies offer individual researchers the ability to rapidly generate large amounts of genome sequence data at dramatically reduced costs. As a result, a need has arisen for new software tools for storage, management and analysis of genome sequence data. Although bioinformatic tools are available for the analysis and management of genome sequences, limitations still remain. For example, restrictions on the submission of data and use of these tools may be imposed, thereby making them unsuitable for sequencing projects that need to remain in-house or proprietary during their initial stages. Furthermore, the availability and use of next generation sequencing in industrial, governmental and academic environments requires biologist to have access to computational support for the curation and analysis of the data generated; however, this type of support is not always immediately available.     

Investigating a macromolecular complex: the toolkit of methods

Structural biologists studying macromolecular complexes spend considerable effort doing strictly "non-structural" work: investigating the physiological relevance and biochemical properties of a complex, preparing homogeneous samples for structural analysis, and experimentally validating structure-based hypotheses regarding function or mechanism. Familiarity with the diverse perspectives and techniques available for studying complexes helps in the critical assessment of non-structural data, expedites the pre-structural characterization of a complex and facilitates the investigation of function. Here we survey the approaches and techniques used to study macromolecular complexes from various viewpoints, including genetics, cell and molecular biology, biochemistry/biophysics, structural biology, and systems biology/bioinformatics. The aim of this overview is to heighten awareness of the diversity of perspectives and experimental tools available for investigating complexes and of their usefulness for the structural biologist.     

A visual environment for the manipulation and integration of JAVA beans

MOTIVATION: Visual programming has the potential to allow non- programmers to redesign and rebuild applications to suit their individual needs. We have built such a visual programming environment, which allows non-programmers to interrogate and combine software components graphically to form new applications. As the needs of the biological community grow, so too will the need for more powerful and easy to use software tools. Intelligent visual programming environments will allow users to design and develop applications easily, so that they can concentrate on the application they wish to build rather than how it is to be done. RESULTS: The environment can read in JAVA Beans, and present relevant information about the beans to the user. The user can then graphically specify how they would like information to flow between the beans by performing simple docking operations. Unnecessary complexities associated with such visual design have been removed by providing intelligent docking of components and visual feedback. With such mechanisms, the complexities of building new applications are reduced. When the biologist has finished the visual construction, the design system is able to generate the new application automatically. The system has been designed specifically to meet the needs of the biological community, and a range of 'BioBeans' are being developed. These include beans for visualization (sequence displays and data visualizers), analysis (feature recognition, error detection) and communication (database access, URL retrieval, DDE communication). AVAILABILITY: Freely available. CONTACT: boyle@synomics.com      

Optimal isn’t good enough

The notion that biological systems come to embody optimal solutions seems consistent with the competitive drive of evolution. It has been used to interpret many examples of sensorimotor behavior. It is attractive from the viewpoint of control engineers because it solves the redundancy problem by identifying the one optimal motor strategy out of many similarly acceptable possibilities. This perspective examines whether there is sufficient basis to apply the formal engineering tools of optimal control to a reductionist understanding of biological systems. For an experimental biologist, this translates into whether the theory of optimal control generates nontrivial and testable hypotheses that accurately predict novel phenomena, ideally at deeper levels of structure than the observable behavior. The methodology of optimal control is applicable when there is (i) a single, known cost function to be optimized, (ii) an invertible model of the plant, and (iii) simple noise interfering with optimal performance. None of these is likely to be true for biological organisms. Furthermore, their motivation is usually good-enough rather than globally optimal behavior. Even then, the performance of a biological organism is often much farther from optimal than the physical limits of its hardware because the brain is continuously testing the acceptable limits of performance as well as just performing the task. This perspective considers an alternative strategy called ??good-enough?? control, in which the organism uses trial-and-error learning to acquire a repertoire of sensorimotor behaviors that are known to be useful, but not necessarily optimal. This leads to a diversity of solutions that tends to confer robustness on the individual organism and its evolution. It is also more consistent with the capabilities of higher sensorimotor structures, such as cerebral cortex, which seems to be designed to classify and recall complex sets of information, thereby allowing the organism to learn from experience, rather than to compute new strategies online. Optimal control has been a useful metaphor for understanding some superficial aspects of motor psychophysics. Reductionists who want to understand the underlying neural mechanisms need to move on.     

MITOMAP: a human mitochondrial genome database--1998 update.

We have continued to develop MITOMAP (http://www.gen.emory. edu/MITOMAP ), a comprehensive database for the human mitochondrial DNA (mtDNA). MITOMAP uses the mtDNA sequence as the unifying element for bringing together information on mitochondrial genome structure and function, pathogenic mutations and their clinical characteristics, population associated variation, and gene-gene interactions. Over the past year we have increased the degree of interlinking of MITOMAP information available on the web page, by using our generalized information management system, GENOME. As increasingly larger regions of the human genome are sequenced and characterized, the need for integrating such information is growing. Consequently, MITOMAP and GENOME provide a valuable reference for the mitochondrial biologist, in addition to being a model for the development of comprehensive, information storage and retrieval systems for other components of the human genome. This paper documents the changes to MITOMAP which have been implemented over the past year.     

生物信息学在植物miRNA研究中的应用

植物miRNA的研究已经从小规模实验向大规模计算分析方向发展,生物信息学的应用成为当前植物miRNA研究的热点问题。本文回顾了最近几年生物信息学在植物miRNA研究中取得的最新进展,简要介绍了植物miRNA的形成及其作用方式,重点对植物miRNA的计算识别、靶基因预测、启动子分析方法进行了讨论,并对相关的数据库资源进行了总结,最后展望了该领域研究的发展方向,将为植物miRNA的计算研究提供理论指导。     

Protein engineering and design

Rapid advances in site-directed mutagenesis and total gene synthesis combined with new expression systems in prokaryotic and eukaryotic cells have provided the molecular biologist with tools for modification of existing proteins to improve catalytic activity, stability and selectivity, for construction of chimeric molecules and for synthesis of completely novel molecules that may be endowed with some useful activity. Such protein engineering can be seen as a cycle in which the structures of engineered molecules are studied by X-ray analysis and two-dimensional nuclear magnetic resonance. The results are used in the improvement of the design by using knowledge-based procedures that exploit facts, rules and observations about proteins of known three-dimensional structure.     

DNA Sequences at a Glance

Data summarization and triage is one of the current top challenges in visual analytics. The goal is to let users visually inspect large data sets and examine or request data with particular characteristics. The need for summarization and visual analytics is also felt when dealing with digital representations of DNA sequences. Genomic data sets are growing rapidly, making their analysis increasingly more difficult, and raising the need for new, scalable tools. For example, being able to look at very large DNA sequences while immediately identifying potentially interesting regions would provide the biologist with a flexible exploratory and analytical tool. In this paper we present a new concept, the “information profile”, which provides a quantitative measure of the local complexity of a DNA sequence, independently of the direction of processing. The computation of the information profiles is computationally tractable: we show that it can be done in time proportional to the length of the sequence. We also describe a tool to compute the information profiles of a given DNA sequence, and use the genome of the fission yeast Schizosaccharomyces pombe strain 972 h⁻ and five human chromosomes 22 for illustration. We show that information profiles are useful for detecting large-scale genomic regularities by visual inspection. Several discovery strategies are possible, including the standalone analysis of single sequences, the comparative analysis of sequences from individuals from the same species, and the comparative analysis of sequences from different organisms. The comparison scale can be varied, allowing the users to zoom-in on specific details, or obtain a broad overview of a long segment. Software applications have been made available for non-commercial use at http://bioinformatics.ua.pt/software/dna-at-glance.     

Recent advances in developing molecular tools for targeted genome engineering of mammalian cells

Various biological molecules naturally existing in diversified species including fungi, bacteria, and bacteriophage have functionalities for DNA binding and processing. The biological molecules have been recently actively engineered for use in customized genome editing of mammalian cells as the molecule-encoding DNA sequence information and the underlying mechanisms how the molecules work are unveiled. Excitingly, multiple novel methods based on the newly constructed artificial molecular tools have enabled modifications of specific endogenous genetic elements in the genome context at efficiencies that are much higher than that of the conventional homologous recombination based methods. This minireview introduces the most recently spotlighted molecular genome engineering tools with their key features and ongoing modifications for better performance. Such ongoing efforts have mainly focused on the removal of the inherent DNA sequence recognition rigidity from the original molecular platforms, the addition of newly tailored targeting functions into the engineered molecules, and the enhancement of their targeting specificity. Effective targeted genome engineering of mammalian cells will enable not only sophisticated genetic studies in the context of the genome, but also widely-applicable universal therapeutics based on the pinpointing and correction of the disease-causing genetic elements within the genome in the near future. [BMB Reports 2015; 48(1): 6-12]