A character set for molecular structure display

A character set is presented with which unscaled 2D molecular structural diagrams can be constructed. A minimal subset has been implemented in ROM on CBM microcomputers, whilst the complete set has been defined as a character font on an ICL PERQ computer. Structural diagrams have also been output on dot-matrix and daisy-wheel printers using appropriate software to print the special characters. The character set provides a simple means of displaying molecular structures on inexpensive microcomputers, on printers and on hardware offering user-definable character fonts.     

Automated comet assay analysis.

BACKGROUND: Recently the "comet assay" or "single-cell gel electrophoresis assay" has been established as a sensitive method for the detection of DNA damage and repair. Most of the software now available to quantify various parameters for DNA damage requires the interaction of a human observer. In this report, we describe an automated analysis system that is based on self-developed software and hardware and needs minimal human interaction. METHODS: The image analysis is divided into two parts: 1) automatic cell recognition and comet classification and 2) quantification of desired comet parameters. Image preprocessing, segmentation, and feature classification were developed with algorithms based on mathematical morphology. To enhance evaluation speed, we have introduced parallel processing of data under the Windows NT operating system (Microsoft Corporation, Redmond, WA). Use of an analogue real-time autofocus unit (B?cker et al.: Phys Med Biol 1997;42:1981-1992) allows for faster analysis. RESULTS: Our recognition software shows a sensitivity of 95.2% and a specificity of 92.7% when tested on test samples from routine work with DNA damage by low-dose radiation (0-2 Gy). The parallel hardware and software concept enables us to analyze 100 comets on one slide in less than 15 min. CONCLUSIONS: A comparison of measurements made on the same samples by manual and automated analysis systems revealed that there are no significant differences. The slope of the dose-response curves and the repair kinetics are very similar and demonstrate that automatic comet assay analysis is possible.     

Imaging workstations for computer-aided primatology: promises and pitfalls

In this paper, the application of biomedical imaging workstations to primatology will be explained and evaluated. The technological basis, computer hardware and software aspects, and the various uses of several types of workstations will all be discussed. The types of workstations include: (1) Simple - these display-only workstations, which function as electronic light boxes, have applications as terminals to picture archiving and communication (PAC) systems. (2) Diagnostic reporting - image-processing workstations that include the ability to perform straightforward manipulations of gray scale and raw data values will be considered for operations such as histogram equalization (whether adaptive or global), gradient edge finders, contour generation, and region of interest, as well as other related functions. (3) Manipulation systems - three-dimensional modeling and computer graphics with application to radiation therapy treatment planning, and surgical planning and evaluation will be considered. A technology of prime importance in the function of these workstations lies in communications and networking. The hierarchical organization of an electronic computer network and workstation environment with the interrelationship of simple, diagnostic reporting, and manipulation workstations to a coaxial or fiber optic network will be analyzed.     

Extensible open source content management systems and frameworks: a solution for many needs of a bioinformatics group

A common challenge for bioinformaticians, in either academic or industry laboratory environments, is providing informatic solutions via the Internet or through a web browser. Recently, the open source community began developing tools for building and maintaining web applications for many disciplines. These content management systems (CMS) provide many of the basic needs of an informatics group, whether in a small company, a group within a larger organisation or an academic laboratory. These tools aid in managing software development, website development, document development, course development, datasets, collaborations and customers. Since many of these tools are extensible, they can be developed to support other research-specific activities, such as handling large biomedical datasets or deploying bioanalytic tools. In this review of open source website management tools, the basic features of content management systems are discussed along with commonly used open source software. Additionally, some examples of their use in biomedical research are given.     

An Innovative Method for Obtaining Consistent Images and Quantification of Histochemically Stained Specimens

Obtaining digital images of color brightfield microscopy is an important aspect of biomedical research and the clinical practice of diagnostic pathology. Although the field of digital pathology has had tremendous advances in whole-slide imaging systems, little effort has been directed toward standardizing color brightfield digital imaging to maintain image-to-image consistency and tonal linearity. Using a single camera and microscope to obtain digital images of three stains, we show that microscope and camera systems inherently produce image-to-image variation. Moreover, we demonstrate that post-processing with a widely used raster graphics editor software program does not completely correct for session-to-session inconsistency. We introduce a reliable method for creating consistent images with a hardware/software solution (ChromaCal™; Datacolor Inc., NJ) along with its features for creating color standardization, preserving linear tonal levels, providing automated white balancing and setting automated brightness to consistent levels. The resulting image consistency using this method will also streamline mean density and morphometry measurements, as images are easily segmented and single thresholds can be used. We suggest that this is a superior method for color brightfield imaging, which can be used for quantification and can be readily incorporated into workflows.     

A theoretical‐experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms,assays, and analysis methods

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists.

     

APBioNet: the Asia-Pacific regional consortium for bioinformatics

Bioinformatics and computational biology, along with the related fields of genomics, proteomics, functional genomics and systems biology are new wave scientific disciplines that harness composite computational power across networks to advance biological knowledge at the most basic level and to direct traditional laboratory-based research efforts in the biomedical sciences. 'Fostering the growth of bioinformatics and allied disciplines in the Asia-Pacific region' is the motto of the first regional bioinformatics society, the Asia-Pacific Bioinformatics Network (APBioNet). APBioNet addresses the issues of hardware, software, databases and networks pertaining to bioinformatics, with the additional layer of pertinent education, training and research. Recent milestones achieved include hosting an international bioinformatics symposium in Asia and setting up large-scale regional grid-computing projects.     

基于PSoC的脑电信号采集系统的设计

脑电信号是一种很重要的生物医学信号,它是临床医学诊断和脑科学研究的一种重要手段。本文介绍了基于Cypress PSoC~(TM)可编程片上系统的脑电信号采集系统的整个设计过程,包括硬件组成和软件设计方法。通过PSoC芯片特有的可编程模拟系统和数字系统,可以把大量的外围器件集成到芯片的内部,从而提高了硬件系统的集成度和可靠性;加上功能强大的PSOC Designer集成开发环境,提高了开发效率,而且系统的软硬件升级也更加容易了。     

GIV: A Tool for Genomic Islands Visualization

A Genomic Islands (GI) is a chunk of DNA sequence in a genome whose origin can be traced back to other organisms or viruses. The detection of GIs plays an indispensable role in biomedical research, due to the fact that GIs are highly related to special functionalities such as disease-causing GIs - pathogenicity islands. It is also very important to visualize genomic islands, as well as the supporting features corresponding to the genomic islands in the genome. We have developed a program, Genomic Island Visualization (GIV), which displays the locations of genomic islands in a genome, as well as the corresponding supportive feature information for GIs. GIV was implemented in C++, and was compiled and executed on Linux/Unix operating systems.

Availability

GIV is freely available for non-commercial use at http://www5.esu.edu/cpsc/bioinfo/software/GIV     

Visualizing biomolecular electrostatics in virtual reality with UnityMol‐APBS

Virtual reality is a powerful tool with the ability to immerse a user within a completely external environment. This immersion is particularly useful when visualizing and analyzing interactions between small organic molecules, molecular inorganic complexes, and biomolecular systems such as redox proteins and enzymes. A common tool used in the biomedical community to analyze such interactions is the Adaptive Poisson‐Boltzmann Solver (APBS) software, which was developed to solve the equations of continuum electrostatics for large biomolecular assemblages. Numerous applications exist for using APBS in the biomedical community including analysis of protein ligand interactions and APBS has enjoyed widespread adoption throughout the biomedical community. Currently, typical use of the full APBS toolset is completed via the command line followed by visualization using a variety of two‐dimensional external molecular visualization software. This process has inherent limitations: visualization of three‐dimensional objects using a two‐dimensional interface masks important information within the depth component. Herein, we have developed a single application, UnityMol‐APBS, that provides a dual experience where users can utilize the full range of the APBS toolset, without the use of a command line interface, by use of a simple graphical user interface (GUI) for either a standard desktop or immersive virtual reality experience.     

Technologies for large-scale physical mapping of human chromosomes

Developing and characterization ordered clone collection from human chromosome specific DNA libraries is proceeding as part of a larger effort to construct a physical map of the entire human genome. The robotics and automation section at Los Alamos has been focussed on developing the hardware and software tools required to support this objective. These tools are typically integrated systems that combine an intuitive user interface, a database, as well as the relevant hardware technologies. To date, we have developed a system to automatically grid clones onto nylon filters in high density arrays. We have also developed a hybridization autoradiograph software scoring tool that combines image analysis, databasing, and a user interface.     

Developing manufacturing control software: A survey and critique

The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping. This paper reviews recent methods for planning, scheduling, simulating, and monitoring the operation of manufacturing systems. A synopsis of the approaches to designing and implementing the real-time control software of these systems is presented. It is concluded that current methodologies support, in a very restricted sense, these planning, scheduling, and monitoring activities, and that enhanced performance can be achieved via an integrated approach.     

BIOSMILE: A semantic role labeling system for biomedical verbs using a maximum-entropy model with automatically generated template features

Background  

Bioinformatics tools for automatic processing of biomedical literature are invaluable for both the design and interpretation of large-scale experiments. Many information extraction (IE) systems that incorporate natural language processing (NLP) techniques have thus been developed for use in the biomedical field. A key IE task in this field is the extraction of biomedical relations, such as protein-protein and gene-disease interactions. However, most biomedical relation extraction systems usually ignore adverbial and prepositional phrases and words identifying location, manner, timing, and condition, which are essential for describing biomedical relations. Semantic role labeling (SRL) is a natural language processing technique that identifies the semantic roles of these words or phrases in sentences and expresses them as predicate-argument structures. We construct a biomedical SRL system called BIOSMILE that uses a maximum entropy (ME) machine-learning model to extract biomedical relations. BIOSMILE is trained on BioProp, our semi-automatic, annotated biomedical proposition bank. Currently, we are focusing on 30 biomedical verbs that are frequently used or considered important for describing molecular events.     

壳聚糖在眼科疾病治疗中的应用

壳聚糖,是一种生物学性优良的多糖类化合物,具有无毒性、生物降解性、组织相容性、理化性质稳定等特性。本文就壳聚糖作为人工泪液、医用粘弹剂、药物缓释系统载体、抗纤维增生药物等的应用进行简要的介绍。     

Future directions in computer simulation

Developments in computer hardware and software are making significant improvements in the availability of simulation for biomedical researchers. This paper reviews past and present techniques for digital computer simulation and looks at improvements likely in the near future. In the area of hardware, personal computers are making computing and simulation more widely available and at the same time, supercomputers and special-purpose numerical processors are making it possible to solve larger problems. Software developments for simulation are reducing the time, effort and special skills required to produce a simulation program. A new hierarchical linker is proposed to make it easy to synthesize a global model by combining existing submodels. In the more distant future, computer models may be constructed graphically and with the assistance of intelligent programs capable of analysis and information retrieval.     

Low-light imaging technology in the life sciences

Photon imaging is an increasingly important technique for the measurement and analysis of chemiluminescence and bioluminescence. New high-performance low-light level imaging systems have recently become available for the life science. These systems use advances in camera design and digital image processing and are now being used for a wide range of luminescence applications. They offer good sensitivity for photon detection and large dynamic range, and are suitable for quantitative analysis. This is achieved using a range of software techniques including image arithmetic, histogramming or summing regions of interest, feature extraction and multiple image processing for kinetics or assay screening. Improvements in imageprocessing hardware and software have increased the usefulness of these systems in the biosciences. Low-light imaging is a rapid and non-invasive method for the sensitive detection and analysis of luminescent assays. As such it offers a powerful and sensitive tool for investigating processes, both at the cellular level (luc and lux reporter genes, intracellular signalling) and for measurement of macro samples (immunoassays, gels and blots, tissue sections).     

Cloud-hosted databases: technologies,challenges and opportunities

One of the main advantages of the cloud computing paradigm is that it simplifies the time-consuming processes of hardware provisioning, hardware purchasing and software deployment. Currently, we are witnessing a proliferation in the number of cloud-hosted applications with a tremendous increase in the scale of the data generated as well as being consumed by such applications. Cloud-hosted database systems powering these applications form a critical component in the software stack of these applications. To better understand the challenges in developing effective cloud-hosted database systems, this article discusses the existing technologies for hosting the database tier of software applications in cloud environments, illustrates their strengths and weaknesses, and presents some opportunities for future work.     

Chapter 16: Text Mining for Translational Bioinformatics

Text mining for translational bioinformatics is a new field with tremendous research potential. It is a subfield of biomedical natural language processing that concerns itself directly with the problem of relating basic biomedical research to clinical practice, and vice versa. Applications of text mining fall both into the category of T1 translational research—translating basic science results into new interventions—and T2 translational research, or translational research for public health. Potential use cases include better phenotyping of research subjects, and pharmacogenomic research. A variety of methods for evaluating text mining applications exist, including corpora, structured test suites, and post hoc judging. Two basic principles of linguistic structure are relevant for building text mining applications. One is that linguistic structure consists of multiple levels. The other is that every level of linguistic structure is characterized by ambiguity. There are two basic approaches to text mining: rule-based, also known as knowledge-based; and machine-learning-based, also known as statistical. Many systems are hybrids of the two approaches. Shared tasks have had a strong effect on the direction of the field. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

What to Learn in This Chapter

Text mining is an established field, but its application to translational bioinformatics is quite new and it presents myriad research opportunities. It is made difficult by the fact that natural (human) language, unlike computer language, is characterized at all levels by rampant ambiguity and variability. Important sub-tasks include gene name recognition, or finding mentions of gene names in text; gene normalization, or mapping mentions of genes in text to standard database identifiers; phenotype recognition, or finding mentions of phenotypes in text; and phenotype normalization, or mapping mentions of phenotypes to concepts in ontologies. Text mining for translational bioinformatics can necessitate dealing with two widely varying genres of text—published journal articles, and prose fields in electronic medical records. Research into the latter has been impeded for years by lack of public availability of data sets, but this has very recently changed and the field is poised for rapid advances. Like all translational bioinformatics software, text mining software for translational bioinformatics can be considered health-critical and should be subject to the strictest standards of quality assurance and software testing.

This article is part of the “Translational Bioinformatics” collection for PLOS Computational Biology.

     

Articulating silences: experiential and biomedical constructions of hypertension symptomatology

In this article, we explore the flexible configuration of a local knowledge system about hypertension symptoms, foregrounding it against prevailing biomedical assertions regarding the asymptomatic or "silent" nature of hypertension. The complex and coherent knowledge system held by older African Americans living in a southern, rural community stands in contrast to the current scientific discourse and local biomedical perspectives on hypertension symptomatology. The older African American participants in this study apply local knowledge of hypertension symptomatology to make health decisions nearly every day. Despite this, most biomedical practitioners maintain a distance from these lay sources of knowledge, often remaining stalwart in their refusal to recognize the existence or influence of symptoms. We conclude that authoritative knowledge ultimately lies in the minds and bodies of the elders, who have encountered symptoms as guideposts that direct action, rather than with a biomedical "reality" that is yet unresolved.     

A Semantic Web management model for integrative biomedical informatics

Background

Data, data everywhere. The diversity and magnitude of the data generated in the Life Sciences defies automated articulation among complementary efforts. The additional need in this field for managing property and access permissions compounds the difficulty very significantly. This is particularly the case when the integration involves multiple domains and disciplines, even more so when it includes clinical and high throughput molecular data.

Methodology/Principal Findings

The emergence of Semantic Web technologies brings the promise of meaningful interoperation between data and analysis resources. In this report we identify a core model for biomedical Knowledge Engineering applications and demonstrate how this new technology can be used to weave a management model where multiple intertwined data structures can be hosted and managed by multiple authorities in a distributed management infrastructure. Specifically, the demonstration is performed by linking data sources associated with the Lung Cancer SPORE awarded to The University of Texas MDAnderson Cancer Center at Houston and the Southwestern Medical Center at Dallas. A software prototype, available with open source at www.s3db.org, was developed and its proposed design has been made publicly available as an open source instrument for shared, distributed data management.

Conclusions/Significance

The Semantic Web technologies have the potential to addresses the need for distributed and evolvable representations that are critical for systems Biology and translational biomedical research. As this technology is incorporated into application development we can expect that both general purpose productivity software and domain specific software installed on our personal computers will become increasingly integrated with the relevant remote resources. In this scenario, the acquisition of a new dataset should automatically trigger the delegation of its analysis.