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Results for “Bioinformatic software”

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At least 145 records · Page 8Linked to original sources

PubMed2026

Protocol to predict gene expression from transcriptomic data using PREDICT.

Linking DNA sequence variation to context-specific transcriptional programs is a critical challenge in regulatory genomics, especially for non-model organisms. Here, we present PREDICT, a modular Python package for discovering cis-regulatory elements and transcription factor binding motifs. We describe steps to identify enriched k-mers from differentially expressed genes, map them to known motifs, quantify their impact on gene expression, and visualize motif co-occurrences. PREDICT provides a robust, k-mer-based approach to uncover regulatory logic in diverse genomic systems. For complete details on the use and execution of this protocol, please refer to Yen et al. and Liu et al.1,2.

Gene Expression Profiling↗

PubMed1995

World Wide Web resources for the biologist.

The World Wide Web is currently the major networking resource for biologists. It has passed Gopher and simple electronic mail (email) servers in popularity. In the 1990s, the advent of client-server software will be the main driving force in bioinformatics. During the past few years, biologists have used the Internet increasingly to distribute data, and the methods of doing this have become more and more sophisticated as the speed with which network links can be made has increased.

Biology↗

PubMed2004

A common open representation of mass spectrometry data and its application to proteomics research.

A broad range of mass spectrometers are used in mass spectrometry (MS)-based proteomics research. Each type of instrument possesses a unique design, data system and performance specifications, resulting in strengths and weaknesses for different types of experiments. Unfortunately, the native binary data formats produced by each type of mass spectrometer also differ and are usually proprietary. The diverse, nontransparent nature of the data structure complicates the integration of new instruments into preexisting infrastructure, impedes the analysis, exchange, comparison and publication of results from different experiments and laboratories, and prevents the bioinformatics community from accessing data sets required for software development. Here, we introduce the 'mzXML' format, an open, generic XML (extensible markup language) representation of MS data. We have also developed an accompanying suite of supporting programs. We expect that this format will facilitate data management, interpretation and dissemination in proteomics research.

Database Management Systems↗

PubMed2006

PseudoViewer: web application and web service for visualizing RNA pseudoknots and secondary structures.

Visualizing RNA secondary structures and pseudoknot structures is essential to bioinformatics systems that deal with RNA structures. However, many bioinformatics systems use heterogeneous data structures and incompatible software components, so integration of software components (including a visualization component) into a system can be hindered by incompatibilities between the components of the system. This paper presents an XML web service and web application program for visualizing RNA secondary structures with pseudoknots. Experimental results show that the PseudoViewer web service and web application are useful for resolving many problems with incompatible software components as well as for visualizing large-scale RNA secondary structures with pseudoknots of any type. The web service and web application are available at http://pseudoviewer.inha.ac.kr/.

Computational Biology↗

PubMed2006

Evolving and experimental technologies in medical imaging.

Medical images are created by detecting radiation probes transmitted through or emitted or scattered by the body. The radiation, modulated through interactions with tissues, yields patterns that provide anatomic and/or physiologic information. X-rays, gamma rays, radiofrequency signals, and ultrasound waves are the standard probes, but others like visible and infrared light, microwaves, terahertz rays, and intrinsic and applied electric and magnetic fields are being explored. Some of the younger technologies, such as molecular imaging, may enhance existing imaging modalities; however, they also, in combination with nanotechnology, biotechnology, bioinformatics, and new forms of computational hardware and software, may well lead to novel approaches to clinical imaging. This review provides a brief overview of the current state of image-based diagnostic medicine and offers comments on the directions in which some of its subfields may be heading.

Animals↗

PubMed2005

[Protein expression profilings of polycystic ovary syndrome].

OBJECTIVE: To screen out serum protein profiling of polycystic ovary syndrome(PCOS) by surface-enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF MS) for discovering the discriminatory proteins. METHODS: Thirty one women with PCOS and thirty healthy women were detected by Weak Cation Exchange(WCX2)chip. ProteinChip reader and Biomarker Wizard software from Ciphergen Inc were combined with a bioinformatics method (support vector machines, SVM ) to analyze protein fingerprinting. RESULTS: There were 4 proteins which were obviously different between the PCOS group and the control. Three of them were up-regulated, and one down-regulated. To set up a analysis model by SVM using the 4 proteins could successfully distinguish between PCOS and the normal control. The corresponding sensitivity, specificity and positive predict value were 86.7%, 83.3%, 87.2%, respectively. CONCLUSION: Using ProteinChip technology can screen out serum discriminatory proteins quickly and efficiently. Combined with SVM, an optimal fingerprinting model has been set up, which can easily predict PCOS. In disease state of PCOS, there are significant variations which consist of four proteins. To investigate those four discriminatory proteins, especially the protein m/z 6 628 may be of benefit to pathogenic study and the development of biomarkers for PCOS.

Adult↗

PubMed2007

[Human esophageal carcinoma antigens screened by serologic analysis of recombinant cDNA expression libraries (SEREX)].

BACKGROUND & OBJECTIVE: In malignant transformation, mutant gene products and dysregulated proteins can become tumor antigens and activate immunoreactions. Therefore, auto-antibodies exist in sera of cancer patients. Serologic analysis of recombinant cDNA expression libraries (SEREX) using autologous and allogenic patient sera provides a powerful approach to identify tumor antigens. This study was to identify esophageal cancer antigens with SEREX for serologic diagnosis, gene therapy, and immune therapy. METHODS: Expression library of cDNA from esophageal squamous cell carcinoma was constructed. SEREX screened out 21 positive clones from the 1.6x10(6) clones in the established library. The 21 positive clones were subcloned to monoclonality and submitted to in vivo excision of pBluescript phagemids. The nucleotide sequences of cDNA inserts were analyzed with DNASIS and BLAST software on EMBL and GenBank. According to the bioinformatics analyses, serologic immunoreactions of 4 colons in 10 samples of esophageal cancer serum and 10 samples of normal control serum were further detected by SADA. RESULTS: Of the 21 positive clones, 4 had no homology to any known genes, 17 were known fragments which were defined as antigens of esophageal cancer for the first time. The serologic immunoreaction rates of 4 selected antigens, including Ribosomal protein S4, and so on, were 40%, 60%, 70%, and 30%, respectively, in cancer sera, and 0%, 10%, 20%, and 20%, respectively, in normal sera. CONCLUSIONS: Antigens, such as Ribosomal protein S4, are frequently involved in serologic immunoreactions of esophageal cancer. The 21 antigens identified by the present study can be used as potential targets for gene therapy and serologic biomarkers of esophageal cancer.

Antibodies, Neoplasm↗

PubMed2006

Urinary proteome of steroid-sensitive and steroid-resistant idiopathic nephrotic syndrome of childhood.

The response to steroid therapy is used to characterize the idiopathic nephrotic syndrome (INS) of childhood as either steroid-sensitive (SSNS) or steroid-resistant (SRNS), a classification with a better prognostic capability than renal biopsy. The majority (approximately 80%) of INS is due to minimal change disease but the percentage of focal and segmental glomerulosclerosis is increasing. We applied a new technological platform to examine the urine proteome to determine if different urinary protein excretion profiles could differentiate patients with SSNS from those with SRNS. Twenty-five patients with INS and 17 control patients were studied. Mid-stream urines were analyzed using surface enhanced laser desorption and ionization mass spectrometry(SELDI-MS). Data were analyzed using multiple bioinformatic techniques. Patient classification was performed using Biomarker Pattern Software and a generalized form of Adaboost and predictive models were generated using a supervised algorithm with cross-validation. Urinary proteomic data distinguished INS patients from control patients, irrespective of steroid response, with a sensitivity of 92.3%, specificity of 93.7%, positive predictive value of 96% and a negative predictive value of 88.2%. Classification of patients as SSNS or SRNS was 100%. A protein of mass 4,144 daltons was identified as the single most important classifier in distinguishing SSNS from SRNS. SELDI-MS combined with bioinformatics can identify different proteomic patterns in INS. Characterization of the proteins of interest identified by this proteomic approach with prospective clinical validation may yield a valuable clinical tool for the non-invasive prediction of treatment response and prognosis.

Adolescent↗

PubMed2003

Building an application framework for integrative genomics.

The accelerated pace of biological research and the current availability of whole-genome data sets provides significant new sources of functional insight. We designed an architecture and framework for software to query and explore such data in an orderly and iterative fashion. The architecture is intended to provide an extensible platform for developing web based bioinformatics applications and to offer a flexible and end-user-extensible software environment to explore and integrate disparate biological data sources. This will enable the user to explore existing relationships and discover new functional relationships among these data.

Computational Biology↗

PubMed2001

The Bioinformatics Template Library--generic components for biocomputing.

MOTIVATION: The efficiency of bioinformatics programmers can be greatly increased through the provision of ready-made software components that can be rapidly combined, with additional bespoke components where necessary, to create finished programs. The new standard for C++ includes an efficient and easy to use library of generic algorithms and data-structures, designed to facilitate low-level component programming. The extension of this library to include functionality that is specifically useful in compute-intensive tasks in bioinformatics and molecular modelling could provide an effective standard for the design of reusable software components within the biocomputing community. RESULTS: A novel application of generic programming techniques in the form of a library of C++ components called the Bioinformatics Template Library (BTL) is presented. This library will facilitate the rapid development of efficient programs by providing efficient code for many algorithms and data-structures that are commonly used in biocomputing, in a generic form that allows them to be flexibly combined with application specific object-oriented class libraries. AVAILABILITY: The BTL is available free of charge from our web site http://www.cryst.bbk.ac.uk/~classlib/ and the EMBL file server http://www.embl-ebi.ac.uk/FTP/index.html

Algorithms↗

PubMed2005

Software agents in molecular computational biology.

Progress made in applying agent systems to molecular computational biology is reviewed and strategies by which to exploit agent technology to greater advantage are investigated. Communities of software agents could play an important role in helping genome scientists design reagents for future research. The advent of genome sequencing in cattle and swine increases the complexity of data analysis required to conduct research in livestock genomics. Databases are always expanding and semantic differences among data are common. Agent platforms have been developed to deal with generic issues such as agent communication, life cycle management and advertisement of services (white and yellow pages). This frees computational biologists from the drudgery of having to re-invent the wheel on these common chores, giving them more time to focus on biology and bioinformatics. Agent platforms that comply with the Foundation for Intelligent Physical Agents (FIPA) standards are able to interoperate. In other words, agents developed on different platforms can communicate and cooperate with one another if domain-specific higher-level communication protocol details are agreed upon between different agent developers. Many software agent platforms are peer-to-peer, which means that even if some of the agents and data repositories are temporarily unavailable, a subset of the goals of the system can still be met. Past use of software agents in bioinformatics indicates that an agent approach should prove fruitful. Examination of current problems in bioinformatics indicates that existing agent platforms should be adaptable to novel situations.

Algorithms↗

PubMed2003

PF-IND: probability algorithm and software for separation of plant and fungal sequences.

The separation of plant and fungal sequences in EST pools by bioinformatic methods is difficult because of sequence similarities between plants and fungi, lack of enough sequence information, and the short length of the isolated fragments. An algorithm and software that utilize the differences in codon usage bias to discriminate between plant and fungal sequences are described. The software (PF-IND) includes five pairs of fungi and their host plants that can be used to analyze a large number of related species. Analysis of a sequence provides an arbitrary value that defines the likelihood that a sequence will be a fungal or a plant gene. The software can distinguish between homologous fungal and plant genes and it helps identify the correct reading frame of unknown expressed sequence tags (ESTs) for which BLAST analyses do not provide clear information. Short sequences of 100-150 bp can be analyzed with high confidence. PF-IND analysis of 100 sequences derived from fungal infected plants identified the origin of 94 sequences. Only 66 sequences were identified by a BLASTX analysis of the same 100 ESTs. Overall, PF-IND is a novel bioinformatic tool aimed at assisting the research of fungus-plant interactions.

Algorithms↗

PubMed2003

GénoPlante-Info (GPI): a collection of databases and bioinformatics resources for plant genomics.

Génoplante is a partnership program between public French institutes (INRA, CIRAD, IRD and CNRS) and private companies (Biogemma, Bayer CropScience and Bioplante) that aims at developing genome analysis programs for crop species (corn, wheat, rapeseed, sunflower and pea) and model plants (Arabidopsis and rice). The outputs of these programs form a wealth of information (genomic sequence, transcriptome, proteome, allelic variability, mapping and synteny, and mutation data) and tools (databases, interfaces, analysis software), that are being integrated and made public at the public bioinformatics resource centre of Génoplante: GénoPlante-Info (GPI). This continuous flood of data and tools is regularly updated and will grow continuously during the coming two years. Access to the GPI databases and tools is available at http://genoplante-info.infobiogen.fr/.

Alleles↗

PubMed2006

Analyzing proteomes and protein function using graphical comparative analysis of tandem mass spectrometry results.

Although generating large amounts of proteomic data using tandem mass spectrometry has become routine, there is currently no single set of comprehensive tools for the rigorous analysis of tandem mass spectrometry results given the large variety of possible experimental aims. Currently available applications are typically designed for displaying proteins and posttranslational modifications from the point of view of the mass spectrometrist and are not versatile enough to allow investigators to develop biological models of protein function, protein structure, or cell state. In addition, storage and dissemination of mass spectrometry-based proteomic data are problems facing the scientific community. To address these issues, we have developed a relational database model that efficiently stores and manages large amounts of tandem mass spectrometry results. We have developed an integrated suite of multifunctional analysis software for interpreting, comparing, and displaying these results. Our system, Bioinformatic Graphical Comparative Analysis Tools (BIGCAT), allows sophisticated analysis of tandem mass spectrometry results in a biologically intuitive format and provides a solution to many data storage and dissemination issues.

Amino Acid Sequence↗

PubMed2002

The Bio* toolkits--a brief overview.

Bioinformatics research is often difficult to do with commercial software. The Open Source BioPerl, BioPython and Biojava projects provide toolkits with multiple functionality that make it easier to create customised pipelines or analysis. This review briefly compares the quirks of the underlying languages and the functionality, documentation, utility and relative advantages of the Bio counterparts, particularly from the point of view of the beginning biologist programmer.

Computational Biology↗

PubMed2006

An object-oriented programming system for the integration of internet-based bioinformatics resources.

The Internet consists of a vast inhomogeneous reservoir of data. Developing software that can integrate a wide variety of different data sources is a major challenge that must be addressed for the realisation of the full potential of the Internet as a scientific research tool. This article presents a semi-automated object-oriented programming system for integrating web-based resources. We demonstrate that the current Internet standards (HTML, CGI [common gateway interface], Java, etc.) can be exploited to develop a data retrieval system that scans existing web interfaces and then uses a set of rules to generate new Java code that can automatically retrieve data from the Web. The validity of the software has been demonstrated by testing it on several biological databases. We also examine the current limitations of the Internet and discuss the need for the development of universal standards for web-based data.

Computational Biology↗

PubMed2006

A Web-based assessment of bioinformatics end-user support services at US universities.

OBJECTIVES: This study was conducted to gauge the availability of bioinformatics end-user support services at US universities and to identify the providers of those services. The study primarily focused on the availability of short-term workshops that introduce users to molecular biology databases and analysis software. METHODS: Websites of selected US universities were reviewed to determine if bioinformatics educational workshops were offered, and, if so, what organizational units in the universities provided them. RESULTS: Of 239 reviewed universities, 72 (30%) offered bioinformatics educational workshops. These workshops were located at libraries (N = 15), bioinformatics centers (N = 38), or other facilities (N = 35). No such training was noted on the sites of 167 universities (70%). Of the 115 bioinformatics centers identified, two-thirds did not offer workshops. CONCLUSIONS: This analysis of university Websites indicates that a gap may exist in the availability of workshops and related training to assist researchers in the use of bioinformatics resources, representing a potential opportunity for libraries and other facilities to provide training and assistance for this growing user group.

Computational Biology↗

PubMed2005

[SSRHunter: development of a local searching software for SSR sites].

Progress in genome research has made it possible to develop new SSR markers by bioinformatics in a relatively narrow region of genome. To realize it, the first thing is to search for potential SSR sites. Any known methods have more or less defects. Efforts were made to develop a local SSR sites searching software in this study. The resultant software, SSRHunter, could accomplish this task perfectly. Furthermore, SSRHunter could provide automatic pretreatment of sequences, routine arrangement of sequences, sequence transformation and convenient report output.

Microsatellite Repeats↗