海洋污损生物数据管理系统的设计与构建

固着或栖息在船舶和人工设施水下部位的海洋污损生物, 会对人们的涉海活动产生不利影响, 其群落的形成和发展过程与温度、盐度、深度、季节、海域、浸海时间、离岸距离和附着基类型等多种因素密切相关。为便于系统分析和综合处理各海区污损生物资料, 理清各要素之间的内在关系, 需要一个能将上述因子与生物群落参数有机地结合起来的数据平台, 将分散、零星的资料予以归纳整合并通过网络共享, 以更好地为生产实践和科学研究服务。本研究采用Internet技术, 应用ASP.NET框架和MySQL数据库, 使用MS Visual Studio 2013设计并开发了服务端部署在Windows 7或Windows Server 2008 R2 (推荐)操作系统上的海洋污损生物数据管理系统, 实现了基于网络的海洋污损生物数据集成、储存与管理, 可完成来源不同、时相变化和海区多样的污损生物数据资料的集成与储存, 能通过单一或多种组合条件进行查询和检索, 并可根据用户的需要导出多种格式的检索结果报表。该系统具备操作简便、方便网络共享、易于升级更新和开拓新功能等特点, 能有效满足科研、生产和管理部门的需要。     

Linking Pharmacokinetics and Biomarker Data to Mechanism of Action in Risk Assessment

Incorporating information on metabolism, pharmacokinetics, and DNA and protein biomarkers provides a means to integrate these important factors into the risk assessment process. Such data are useful for species to species extrapolation, high- to low-dose extrapolation and PBPK modeling. In addition, these data are critical for understanding the mode of action for chemical carcinogens. Through the use of mass spectrometry, stable isotopes can be used to unequivocally demonstrate pathways of formation of biomarkers and relationships between exogenous and endogenous processes. This paper reviews what has been learned for two carcinogens, vinyl chloride and butadiene. It is clear that such data play major roles in improving the understanding of how chemicals cause cancer, extending the range of data on exposure-response relationships, and examining interspecies differences and inter-individual differences that may affect susceptibility. As such, it is also clear that these data play a critical role in improving the accuracy of risk assessments.     

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery

Background  

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication.     

Pathway analysis in metabolic databases via differential metabolic display (DMD)

MOTIVATION: A number of metabolic databases are available electronically, some with features for querying and visualizing metabolic pathways and regulatory networks. We present a unifying, systematic approach based on PETRI nets for storing, displaying, comparing, searching and simulating such nets from a number of different sources. RESULTS: Information from each data source is extracted and compiled into a PETRI net. Such PETRI nets then allow to investigate the (differential) content in metabolic databases, to map and integrate genomic information and functional annotations, to compare sequence and metabolic databases with respect to their functional annotations, and to define, generate and search paths and pathways in nets. We present an algorithm to systematically generate all pathways satisfying additional constraints in such PETRI nets. Finally, based on the set of valid pathways, so-called differential metabolic displays (DMDs) are introduced to exhibit specific differences between biological systems, i.e. different developmental states, disease states, or different organisms, on the level of paths and pathways. DMDs will be useful for target finding and function prediction, especially in the context of the interpretation of expression data.     

Intermittent Androgen Suppression: Estimating Parameters for Individual Patients Based on Initial PSA Data in Response to Androgen Deprivation Therapy

When a physician decides on a treatment and its schedule for a specific patient, information gained from prior patients and experience in the past is taken into account. A more objective way to make such treatment decisions based on actual data would be useful to the clinician. Although there are many mathematical models proposed for various diseases, so far there is no mathematical method that accomplishes optimization of the treatment schedule using the information gained from past patients or “rapid learning” technology. In an attempt to use this approach, we integrate the information gained from patients previously treated with intermittent androgen suppression (IAS) with that from a current patient by first fitting the time courses of clinical data observed from the previously treated patients, then constructing the prior information of the parameter values of the mathematical model, and finally, maximizing the posterior probability for the parameters of the current patient using the prior information. Although we used data from prostate cancer patients, the proposed method is general, and thus can be applied to other diseases once an appropriate mathematical model is established for that disease.     

The use of transepithelial models to examine host-pathogen interactions

Many pathogens must overcome an epithelial barrier in order to establish an infection. Unsurprisingly, such pathogens have evolved different mechanisms to overcome this obstacle, targeting specific epithelial structures or functions. These include disruption of epithelial barrier function, transcytosing from the apical to the basolateral membrane domain or inducing cell movement such as neutrophil recruitment. When studying these processes in vivo, animal models often fail to mimic the disease observed in humans and present a complex system in which many variables cannot be controlled. Therefore, in vitro transepithelial models that permit the study of a relevant biological surface have been developed, to integrate not only interactions between bacteria and epithelial cells but also, under certain conditions, to integrate a third cell type, such as neutrophils or dendritic cells. Such models are particularly useful for studying the bacteria-host relationship as it would occur in the microenvironment of the human epithelium and have enhanced our understanding of the unique strategies by which pathogenic bacteria exploit host cells to overcome the initial epithelial hurdle.     

Improving knowledge of plant tissue culture and media formulation by neurofuzzy logic: a practical case of data mining using apricot databases

Plant tissue growth can be regulated and controlled via culture media composition. A number of different laborious and time-consuming approaches have been used to attempt development of optimized media for a wide range of species and applications. However, plant tissue culture is a very complex task, and the identification of the influences of process factors such as mineral nutrients or plant growth regulators on a wide spectrum of growth responses cannot always well comprehended.This study employs a new approach, data mining, to uncover and integrate knowledge hidden in multiple data from plant tissue culture media formulations using apricot micropropagation databases as an example. Neurofuzzy logic technology made it possible to identify relationships among several factors (cultivars, mineral nutrients and plant growth regulators) and growth parameters (shoots number, shoots length and productivity), extracting biologically useful information from each database and combining them to create a model. The IF-THEN rule sets generated by neurofuzzy logic were completely in agreement with previous findings based on statistical analysis, but advantageously generated understandable and reusable knowledge that can be applied in future plant tissue culture media optimization.     

Some Considerations on Data Integration for the Next-Generation Flora (iFlora) and Flora Revision—— A Case Study of Gaultheria (Ericaceae)

The next-generation intelligent Flora (iFlora) is designed to integrate current botanical knowledge, with molecular biology information and computer technology. The most important and urgent task for iFlora development is to search for an approach to incorporate all useful data into an accurate, most up-to-date and complete information database for a taxon, and hierarchically classify these data to meet different demands from iFlora users, to provide the user an authentic, scientific research based platform for sharing botanic knowledge, and associated valuable information for the benefit of national economy and quality of our life. In this study, we summarized the innovations, hierarchical classifications and functions of data for iFlora, in contrast of that of the previous Floras and the frequently used digital plant databases or eFloras. The innovation and essential of data compilation and integration of the iFlora was emphasized as intelligent assembly of data from DNA barcodes, key morphological characters, digital images and molecular phylogenetics with the support of computer techniques to achieve intelligent plant identification. We attempted to integrate previously assembled research data into the iFlora, and list three hierarchically classified data and their functions, and related issues, with the genus Gaultheria and one of its species, G.hookeri, as test case.     

iFlora与植物志修订的若干思考——以杜鹃花科白珠树属为例

结合现代植物学、DNA测序与信息等关键技术而产生的新一代智能植物志（iFlora）,其研发中最首要和迫切的任务之一就是如何将前沿、准确和完善的植物数据信息进行特色整合及智能化处理,为用户提供一个客观而科学的,具理论和实际应用为一体的植物学知识共享平台,并有效地为国民经济发展提供有价值的植物资源信息渠道。本文简要介绍了与传统植物志和目前常用的电子植物志数据库相区别的iFlora数据信息的分级内容、特点和功能,并强调了作为iFlora的核心数据信息,即用于物种鉴定的植物DNA条形码、关键形态学分类特征、植物图像等识别数据,以及分子系统发育数据等。以杜鹃花科（Ericaceae）白珠树属（Gaultheria）和其属下红粉白珠（G.hookeri）为例,介绍了iFlora采用的三类数据（核心数据、基础数据和拓展数据）构成的三级信息及其功能,同时探讨了信息整合时可能遇到的问题。     

HCOP: a searchable database of human orthology predictions

The HUGO Gene Nomenclature Committee (HGNC) Comparison of Orthology Predictions (HCOP) search tool combines the human, mouse, rat and chicken orthology assertions made by PhIGs, HomoloGene, Ensembl, Inparanoid, Mouse Genome Informatics (MGI) and HGNC, enabling users to identify predicted ortholog pairs for a specified gene or genes. The HCOP resource provides a useful method to integrate, compare and access a variety of disparate sources of human orthology data. The HCOP search tool, data and documentation are available at http://www.gene.ucl.ac.uk/hcop.     

Sequential adaptive variables and subject selection for GEE methods

Modeling correlated or highly stratified multiple-response data is a common data analysis task in many applications, such as those in large epidemiological studies or multisite cohort studies. The generalized estimating equations method is a popular statistical method used to analyze these kinds of data, because it can manage many types of unmeasured dependence among outcomes. Collecting large amounts of highly stratified or correlated response data is time-consuming; thus, the use of a more aggressive sampling strategy that can accelerate this process—such as the active-learning methods found in the machine-learning literature—will always be beneficial. In this study, we integrate adaptive sampling and variable selection features into a sequential procedure for modeling correlated response data. Besides reporting the statistical properties of the proposed procedure, we also use both synthesized and real data sets to demonstrate the usefulness of our method.     

The muddle of ages,turnover, transit,and residence times in the carbon cycle

Comparisons among ecosystem models or ecosystem dynamics along environmental gradients commonly rely on metrics that integrate different processes into a useful diagnostic. Terms such as age, turnover, residence, and transit times are often used for this purpose; however, these terms are variably defined in the literature and in many cases, calculations ignore assumptions implicit in their formulas. The aim of this opinion piece was i) to make evident these discrepancies and the incorrect use of formulas, ii) highlight recent results that simplify calculations and may help to avoid confusion, and iii) propose the adoption of simple and less ambiguous terms.     

Construction of integrated genetic linkage maps by means of a new computer package: Join Map

A computerized procedure to contruct integrate genetic maps is presented. The computer program (J oin M ap ) can handle raw data from F₂s, backcrosses and recombinant inbred lines, as well as listed pair-wise recombination frequencies. The procedure is useful for combining linkage data that have been collected in different experiments; the result is a mathematical alignment of the distinct genetic maps. Data from single experiments can be dealt with as well. In view of the fast growing amount of linkage information for molecular markers, which is often being generated by different research groups, integrated maps provide useful information on the map position of genes and DNA markers.
The procedure performs a sequential build-up of the map and, at each step, a numerical search for the best fitting order of markers. Weighted least squares is used for the estimation of map distances.     

SIDEKICK: Genomic data driven analysis and decision-making framework

Background  

Scientists striving to unlock mysteries within complex biological systems face myriad barriers in effectively integrating available information to enhance their understanding. While experimental techniques and available data sources are rapidly evolving, useful information is dispersed across a variety of sources, and sources of the same information often do not use the same format or nomenclature. To harness these expanding resources, scientists need tools that bridge nomenclature differences and allow them to integrate, organize, and evaluate the quality of information without extensive computation.     

Ecosystem services and biodiversity conservation: concepts and a glossary

The RUBICODE project draws on expertise from a range of disciplines to develop and integrate frameworks for assessing the impacts of environmental change on ecosystem service provision, and for rationalising biodiversity conservation in that light. With such diverse expertise and concepts involved, interested parties will not be familiar with all the key terminology. This paper defines the terms as used within the project and, where useful, discusses some reasoning behind the definitions. Terms are grouped by concept rather than being listed alphabetically.     

Mathematical models of the balance between apoptosis and proliferation

As our understanding of cellular behaviour grows, and we identify more and more genes involved in the control of such basic processes as cell division and programmed cell death, it becomes increasingly difficult to integrate such detailed knowledge into a meaningful whole. This is an area where mathematical modelling can complement experimental approaches, and even simple mathematical models can yield useful biological insights. This review presents examples of this in the context of understanding the combined effects of different levels of cell death and cell division in a number of biological systems including tumour growth, the homeostasis of immune memory and pre-implantation embryo development. The models we describe, although simplistic, yield insight into several phenomena that are difficult to understand using a purely experimental approach. This includes the different roles played by the apoptosis of stem cells and differentiated cells in determining whether or not a tumour can grow; the way in which a density dependent rate of apoptosis (for instance mediated by cell-cell contact or cytokine signalling) can lead to homeostasis; and the effect of stochastic fluctuations when the number of cells involved is small. We also highlight how models can maximize the amount of information that can be extracted from limited experimental data. The review concludes by summarizing the various mathematical frameworks that can be used to develop new models and the type of biological information that is required to do this.     

Detection of Optogenetic Stimulation in Somatosensory Cortex by Non-Human Primates - Towards Artificial Tactile Sensation

Neuroprosthesis research aims to enable communication between the brain and external assistive devices while restoring lost functionality such as occurs from stroke, spinal cord injury or neurodegenerative diseases. In future closed-loop sensorimotor prostheses, one approach is to use neuromodulation as direct stimulus to the brain to compensate for a lost sensory function and help the brain to integrate relevant information for commanding external devices via, e.g. movement intention. Current neuromodulation techniques rely mainly of electrical stimulation. Here we focus specifically on the question of eliciting a biomimetically relevant sense of touch by direct stimulus of the somatosensory cortex by introducing optogenetic techniques as an alternative to electrical stimulation. We demonstrate that light activated opsins can be introduced to target neurons in the somatosensory cortex of non-human primates and be optically activated to create a reliably detected sensation which the animal learns to interpret as a tactile sensation localized within the hand. The accomplishment highlighted here shows how optical stimulation of a relatively small group of mostly excitatory somatosensory neurons in the nonhuman primate brain is sufficient for eliciting a useful sensation from data acquired by simultaneous electrophysiology and from behavioral metrics. In this first report to date on optically neuromodulated behavior in the somatosensory cortex of nonhuman primates we do not yet dissect the details of the sensation the animals exerience or contrast it to those evoked by electrical stimulation, issues of considerable future interest.