Infrastructure for the life sciences: design and implementation of the UniProt website

Background  

The UniProt consortium was formed in 2002 by groups from the Swiss Institute of Bioinformatics (SIB), the European Bioinformatics Institute (EBI) and the Protein Information Resource (PIR) at Georgetown University, and soon afterwards the website was set up as a central entry point to UniProt resources. Requests to this address were redirected to one of the three organisations' websites. While these sites shared a set of static pages with general information about UniProt, their pages for searching and viewing data were different. To provide users with a consistent view and to cut the cost of maintaining three separate sites, the consortium decided to develop a common website for UniProt. Following several years of intense development and a year of public beta testing, the domain was switched to the newly developed site described in this paper in July 2008.     

Data clustering in life sciences

Clustering has a wide range of applications in life sciences and over the years has been used in many areas ranging from the analysis of clinical information, phylogeny, genomics, and proteomics. The primary goal of this article is to provide an overview of the various issues involved in clustering large biological datasets, describe the merits and underlying assumptions of some of the commonly used clustering approaches, and provide insights on how to cluster datasets arising in various areas within life sciences. We also provide a brief introduction to Cluto, a general purpose toolkit for clustering various datasets, with an emphasis on its applications to problems and analysis requirements within life sciences.     

Genomics in space life sciences

Since the early days of manned spaceflight, hazardous effects of the space environment on living organisms have been disputed. With the continuous manning of the International Space Station, the planned Chinese space station, and renewed interest in returning to the Moon and sending manned flights to Mars, identifying and addressing the potential outcomes of long-term space exposures is critically important.     

Synchrotron radiation in life sciences

Synchrotron Radiation (SR) presents itself as a "play-ground" with a large range of methods and techniques suitable to unveil the mysteries of life. Here we attempt to present a few of these methods that complement those employed in the home laboratory. SR diffraction, spectroscopy and imaging methods relevant to the atomic structure determination and characterization of the properties and function of chemical compounds and macromolecules of biological relevance, are introduced.     

Opportunities and challenges for the life sciences community

Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19-20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16-17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org ) was formed to become a Digital Commons for the life sciences community.     

基因组研究与生命科学工业的崛起

人类基因组的全序列测定预计可提前两年于２００３年完成，特别是基因组内的蛋白质编码序列将更早测定。私人财团斥巨资进入这个领域，并望抢得先手，这意味着基因组研究可创造巨大财富。在过去几年里，国际上一批知名的大型制药集团和化学工业公司已在基因组研究领域内投入大量资金，并形成了一个新的产业部门，即生命科学工业。制药工业是生命科学工业的主要支柱之一，与基因组研究的关系特别密切。药物基因组学研究表明，药物的疗效与患者的基因型相关，因此，今后的药物生产要考虑到药物投放地区人群中有关的等位基因的频率，医疗处方也将因人而异而趋向个人化。比较基因组学研究则有助于从模式生物的资料指出与疾病可能相关的基因，可以此作为靶标来设计药物。     

Photo acoustic in life sciences

Photoacoustic (PA) measurements provide, by the very nature of the PA effect, the possibility to obtain information on the optical and thermal properties of samples. In addition they can yield information on the enthalpy changes and characteristic times involved in photo-induced processes as the acoustic signal in proportional to the heat produced following the absorption of the modulated excitation. In the study of optical properties the relative insensitivity to scattered light of the PA signal makes such measurement an attractive way to measure biological samples in vivo, or, at least, withpout the need to isolated the absorbing compounds. The dependence of the PA signal on the thermal properties of the sample is particularly useful when heterogeneous samples are studied. As a photocalorimetric method the technique shows considerable promise in the study of photo-biogenergetics, especially photosynthesis. Only in special cases can analytical applications of the method compete with fluorescence measurements (for detection), and with increasingly sophisticated optical transmission and reflectance techniques (for identification). However, the PA method may find important uses in fundamental research and in applied areas such as biomedicine and agricultural biochemistry.     

Data issues in the life sciences

We review technical and sociological issues facing the Life Sciences as they transform into more data-centric disciplines - the "Big New Biology". Three major challenges are: 1) lack of comprehensive standards; 2) lack of incentives for individual scientists to share data; 3) lack of appropriate infrastructure and support. Technological advances with standards, bandwidth, distributed computing, exemplar successes, and a strong presence in the emerging world of Linked Open Data are sufficient to conclude that technical issues will be overcome in the foreseeable future. While motivated to have a shared open infrastructure and data pool, and pressured by funding agencies in move in this direction, the sociological issues determine progress. Major sociological issues include our lack of understanding of the heterogeneous data cultures within Life Sciences, and the impediments to progress include a lack of incentives to build appropriate infrastructures into projects and institutions or to encourage scientists to make data openly available.     

New essential trace elements for the life sciences

Biological Trace Element Research - The possible importance of some new essential trace elements in nutrition is discussed. Most likely, insufficient intake of a specific trace element becomes...     

Laser tweezers and multiphoton microscopes in life sciences

Near infrared (NIR) laser microscopy enables optical micromanipulation, piconewton force determination, and sensitive fluorescence studies by laser tweezers. Otherwise, fluorescence images with high spatial and temporal resolution of living cells and tissues can be obtained via non-resonant fluorophore excitation with multiphoton NIR laser scanning microscopes. Furthermore, NIR femtosecond laser pulses at TW/cm2 intensities can be used to realize non-invasive contact-free surgery of nanometer-sized structures within living cells and tissues. Applications of these novel versatile NIR laser-based tools for the determination of motility forces, coenzyme and chlorophyll imaging, three-dimensional multigene detection, non-invasive optical sectioning of tissues ("optical biopsy"), functional protein imaging, and nanosurgery of chromosomes are described.