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Bioinformatics dumped with wikiteam3 tools.

Bioinformatics dumped with wikiteam3 tools.

Bioinformatics dumped with wikiteam3 tools.

Bioinformatics dumped with wikiteam3 tools.

Tri 2 2016/2017

Tri 2 2016/2017

Event Date: 27 March 2014 Room B01 Clore Management Centre Birkbeck, University of London Malet Street London WC1E 7HX The Department of Biological Sciences at Birkbeck presents: The 2014 Bernal Lecture Professor Dame Janet Thornton…

Event Date: 27 March 2014 Room B01 Clore Management Centre Birkbeck, University of London Malet Street London WC1E 7HX The Department of Biological Sciences at Birkbeck presents: The 2014 Bernal Lecture Professor Dame Janet Thornton…

Bioinformatics is the discovery, development and application of computers to help solve important biological problems. The Bioinformatics Research Center is located on Charlotte Research Institute Campus of UNC Charlotte. As the first Leadership in Energy and Environmental Design (LEED) certified building on campus, it offers space for both wet and dry laboratories, and includes core facilities for molecular biology, proteomics, and computing. Additional genomics and proteomics core facilities are available through a UNC Charlotte partnership with the Carolinas Medical Center. For more information, visit http://bioinformatics.uncc.edu.

Data Protection Record of Processing Activities and Privacy Notice generator toolkit by EMBL’s European Bioinformatics Institute

Data Protection Record of Processing Activities and Privacy Notice generator toolkit by EMBL’s European Bioinformatics Institute

Data Protection Record of Processing Activities and Privacy Notice generator toolkit by EMBL’s European Bioinformatics Institute

The comparison of computer generated protein structural models is an important element of protein structure prediction. It has many uses including model quality evaluation, selection of the final models from a large set of candidates or optimisation of parameters of energy functions used in template-free modelling and refinement. Although many protein comparison methods are available online on numerous web servers, they are not well suited for large scale model comparison: (1) they operate with methods designed to compare actual proteins, not the models of the same protein, (2) majority of them offer only a single pairwise structural comparison and are unable to scale up to a required order of thousands of comparisons. To bridge the gap between the protein and model structure comparison we have developed the Protein Models Comparator (pm-cmp). To be able to deliver the scalability on demand and handle large comparison experiments the pm-cmp was implemented "in the cloud". Protein Models Comparator is a scalable web application for a fast distributed comparison of protein models with RMSD, GDT TS, TM-score and Q-score measures. It runs on the Google App Engine (GAE) cloud platform and is a showcase of how the emerging PaaS (Platform as a Service) technology could be used to simplify the development of scalable bioinformatics services. The functionality of pm-cmp is accessible through API which allows a full automation of the experiment submission and results retrieval. Protein Models Comparator is free software released on the Affero GNU Public Licence and is available with its source code at: http://www.infobiotics.org/pm-cmp This article presents a new web application addressing the need for a large-scale model-specific protein structure comparison and provides an insight into the GAE (Google App Engine) platform and its usefulness in scientific computing.

Perl 2001 Beginning Perl For Bioinformatics EN

James Ferguson http://lca2018.linux.org.au/schedule/presentation/200/ The not so secret source of bioinformatics This talk was given at Linux.conf.au 2018 (LCA2018) which was held on 22-26 January 2018 in Sydney Australia. linux.conf.au is a conference about the Linux operating system, and all aspects of the thriving ecosystem of Free and Open Source Software that has grown up around it. Run since 1999, in a different Australian or New Zealand city each year, by a team of local volunteers, LCA invites more than 500 people to learn from the people who shape the future of Open Source. For more information on the conference see https://linux.conf.au/ #linux.conf.au #linux #foss #opensource

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

The 14-base pair hypervariable region in mitochondrial DNA (mtDNA) of Asian populations, specifically Japanese and Chinese students at Plattsburgh State University, was examined. Previous research on this 14-base pair region showed it to be susceptible to mutations and as a result indicated direct correlation with specific ethnic populations. Earlier studies provided the 14-base pair region sequence analysis for Asians in general. This inquiry-based project was generated in a junior/senior college general genetics course. The project produced sequences of the 14-base pair hypervariable region for Japanese and Chinese populations, specifically. The investigation examined 28 Japanese and 27 Chinese international students. A Control group, consisting of 20 random students was also sampled. The 14-base pair hypervariable region for each sample was analyzed through comparison using bioinformatics. Analyzing the samples showed that, overall, 46% of the Japanese samples, 59% of the Chinese samples, and 75% of the Control samples had the same 14-base pair sequence. In addition to this, it was observed that the Japanese, Chinese, and Control group all had their own specific mutations within the 14-base pair hypervariable region. (Contains 3 figures and 2 tables.)

Bioinformatics Books 2005 看看 生信算法讲义 CN

Bioinformatics Books 2005 看看 生信算法讲义 CN

This article is from PLoS ONE , volume 9 . Abstract Setting: During endoplasmic reticulum (ER) stress, the endoribonuclease (RNase) Ire1α initiates removal of a 26 nt region from the mRNA encoding the transcription factor Xbp1 via an unconventional mechanism (atypically within the cytosol). This causes an open reading frame-shift that leads to altered transcriptional regulation of numerous downstream genes in response to ER stress as part of the unfolded protein response (UPR). Strikingly, other examples of targeted, unconventional splicing of short mRNA regions have yet to be reported. Objective: Our goal was to develop an approach to identify non-canonical, possibly very short, splicing regions using RNA-Seq data and apply it to ER stress-induced Ire1α heterozygous and knockout mouse embryonic fibroblast (MEF) cell lines to identify additional Ire1α targets. Results: We developed a bioinformatics approach called the Read-Split-Walk (RSW) pipeline, and evaluated it using two Ire1α heterozygous and two Ire1α-null samples. The 26 nt non-canonical splice site in Xbp1 was detected as the top hit by our RSW pipeline in heterozygous samples but not in the negative control Ire1α knockout samples. We compared the Xbp1 results from our approach with results using the alignment program BWA, Bowtie2, STAR, Exonerate and the Unix “grep” command. We then applied our RSW pipeline to RNA-Seq data from the SKBR3 human breast cancer cell line. RSW reported a large number of non-canonical spliced regions for 108 genes in chromosome 17, which were identified by an independent study. Conclusions: We conclude that our RSW pipeline is a practical approach for identifying non-canonical splice junction sites on a genome-wide level. We demonstrate that our pipeline can detect novel splice sites in RNA-Seq data generated under similar conditions for multiple species, in our case mouse and human.

This article is from Frontiers in Genetics , volume 5 . Abstract Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of (i) warranting the integration and the traceability of data, (ii) ensuring the correct processing and analyses of genomic data, and (iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.

This article is from Chinese Medicine , volume 9 . Abstract Background: Frankincense (Boswellia carterii, known as Ru Xiang in Chinese) and sandalwood (Santalum album, known as Tan Xiang in Chinese) are cancer preventive and therapeutic agents in Chinese medicine. Their biologically active ingredients are usually extracted from frankincense by hydrodistillation and sandalwood by distillation. This study aims to investigate the anti-proliferative and pro-apoptotic activities of frankincense and sandalwood essential oils in cultured human bladder cancer cells. Methods: The effects of frankincense (1,400–600 dilutions) (v/v) and sandalwood (16,000–7,000 dilutions) (v/v) essential oils on cell viability were studied in established human bladder cancer J82 cells and immortalized normal human bladder urothelial UROtsa cells using a colorimetric XTT cell viability assay. Genes that responded to essential oil treatments in human bladder cancer J82 cells were identified using the Illumina Expression BeadChip platform and analyzed for enriched functions and pathways. The chemical compositions of the essential oils were determined by gas chromatography–mass spectrometry. Results: Human bladder cancer J82 cells were more sensitive to the pro-apoptotic effects of frankincense essential oil than the immortalized normal bladder UROtsa cells. In contrast, sandalwood essential oil exhibited a similar potency in suppressing the viability of both J82 and UROtsa cells. Although frankincense and sandalwood essential oils activated common pathways such as inflammatory interleukins (IL-6 signaling), each essential oil had a unique molecular action on the bladder cancer cells. Heat shock proteins and histone core proteins were activated by frankincense essential oil, whereas negative regulation of protein kinase activity and G protein-coupled receptors were activated by sandalwood essential oil treatment. Conclusion: The effects of frankincense and sandalwood essential oils on J82 cells and UROtsa cells involved different mechanisms leading to cancer cell death. While frankincense essential oil elicited selective cancer cell death via NRF-2-mediated oxidative stress, sandalwood essential oil induced non-selective cell death via DNA damage and cell cycle arrest.

This article is from BMC Bioinformatics , volume 13 . Abstract Background: Bioinformatics services have been traditionally provided in the form of a web-server that is hosted at institutional infrastructure and serves multiple users. This model, however, is not flexible enough to cope with the increasing number of users, increasing data size, and new requirements in terms of speed and availability of service. The advent of cloud computing suggests a new service model that provides an efficient solution to these problems, based on the concepts of "resources-on-demand" and "pay-as-you-go". However, cloud computing has not yet been introduced within bioinformatics servers due to the lack of usage scenarios and software layers that address the requirements of the bioinformatics domain. Results: In this paper, we provide different use case scenarios for providing cloud computing based services, considering both the technical and financial aspects of the cloud computing service model. These scenarios are for individual users seeking computational power as well as bioinformatics service providers aiming at provision of personalized bioinformatics services to their users. We also present elasticHPC, a software package and a library that facilitates the use of high performance cloud computing resources in general and the implementation of the suggested bioinformatics scenarios in particular. Concrete examples that demonstrate the suggested use case scenarios with whole bioinformatics servers and major sequence analysis tools like BLAST are presented. Experimental results with large datasets are also included to show the advantages of the cloud model. Conclusions: Our use case scenarios and the elasticHPC package are steps towards the provision of cloud based bioinformatics services, which would help in overcoming the data challenge of recent biological research. All resources related to elasticHPC and its web-interface are available at http://www.elasticHPC.org.

This article is from Bioinformatics , volume 28 . Abstract Summary: We developed MolBioLib to address the need for adaptable next-generation sequencing analysis tools. The result is a compact, portable and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. MolBioLib is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib has been used to identify causative single-nucleotide polymorphisms in whole genome sequencing, detect balanced chromosomal rearrangements and compute enrichment of messenger RNAs (mRNAs) on microtubules, typically requiring applications of under 200 lines of code. MolBioLib includes programs to perform a wide variety of analysis tasks, such as computing read coverage, annotating genomic intervals and novel peak calling with a wavelet algorithm. Although MolBioLib was designed primarily for bioinformatics purposes, much of its functionality is applicable to a wide range of problems. Complete documentation and an extensive automated test suite are provided.Availability: MolBioLib is available for download at: http://sourceforge.net/projects/molbiolibContact: [email protected]

Bioinformatics Codes dumped with WikiTeam tools.

Bioinformatics Codes dumped with WikiTeam tools.

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset.

The outcome of a functional genomics pipeline is usually a partial list of genomic features, ranked by their relevance in modelling biological phenotype in terms of a classification or regression model. Due to resampling protocols or just within a meta-analysis comparison, instead of one list it is often the case that sets of alternative feature lists (possibly of different lengths) are obtained. Here we introduce a method, based on the algebraic theory of symmetric groups, for studying the variability between lists ("list stability") in the case of lists of unequal length. We provide algorithms evaluating stability for lists embedded in the full feature set or just limited to the features occurring in the partial lists. The method is demonstrated first on synthetic data in a gene filtering task and then for finding gene profiles on a recent prostate cancer dataset.

To facilitate flexible and efficient structural bioinformatics analyses, new functionality for three-dimensional structure processing and analysis has been introduced into PyCogent -- a popular feature-rich framework for sequence-based bioinformatics, but one which has lacked equally powerful tools for handling stuctural/coordinate-based data. Extensible Python modules have been developed, which provide object-oriented abstractions (based on a hierarchical representation of macromolecules), efficient data structures (e.g. kD-trees), fast implementations of common algorithms (e.g. surface-area calculations), read/write support for Protein Data Bank-related file formats and wrappers for external command-line applications (e.g. Stride). Integration of this code into PyCogent is symbiotic, allowing sequence-based work to benefit from structure-derived data and, reciprocally, enabling structural studies to leverage PyCogent's versatile tools for phylogenetic and evolutionary analyses.

To facilitate flexible and efficient structural bioinformatics analyses, new functionality for three-dimensional structure processing and analysis has been introduced into PyCogent -- a popular feature-rich framework for sequence-based bioinformatics, but one which has lacked equally powerful tools for handling stuctural/coordinate-based data. Extensible Python modules have been developed, which provide object-oriented abstractions (based on a hierarchical representation of macromolecules), efficient data structures (e.g. kD-trees), fast implementations of common algorithms (e.g. surface-area calculations), read/write support for Protein Data Bank-related file formats and wrappers for external command-line applications (e.g. Stride). Integration of this code into PyCogent is symbiotic, allowing sequence-based work to benefit from structure-derived data and, reciprocally, enabling structural studies to leverage PyCogent's versatile tools for phylogenetic and evolutionary analyses.

Journal of Research of the National Institute of Standards and Technology

Journal of Research of the National Institute of Standards and Technology

Journal of Research of the National Institute of Standards and Technology

Journal of Research of the National Institute of Standards and Technology

Acinetobacter baumannii is a bacterial pathogen of increasing medical significance in military and civilian healthcare facilities. The importance of A. baumannii infections in war-related injuries is well established. A. baumannii was the most common gram-negative bacillus recovered from traumatic injuries to the lower extremities during the Vietnam War. More recently a new series of infections was reported in U.S. service personnel injured in the Iraq/Kuwait/Afghanistan regions during Operation Iraqi Freedom and in Afghanistan during Operation Enduring Freedom and many of these isolates expressed a high degree of antimicrobial resistance. In addition, the incidence of multidrug-resistant (MDR) A. baumannii infections, associated with significant morbidity and mortality, are increasing worldwide. Thus there is a critical need to identify potential vaccine antigens and new drug targets expressed by A. baumannii. In the past year we have made significant progress in our research. We identified three surface polysaccharides and three proteins that may serve as vaccine candidates and/or drug targets. We have developed an animal model that will allow us to test the se bacterial components in vivo. Finally, we completely sequenced and annotated the genome of A. baumannii 307, which allows us to search for novel targets in silico.

Acinetobacter baumannii is a bacterial pathogen of increasing medical significance in military and civilian healthcare facilities. The importance of A. baumannii infections in war-related injuries is well established. A. baumannii was the most common gram-negative bacillus recovered from traumatic injuries to the lower extremities during the Vietnam War. More recently a new series of infections was reported in U.S. service personnel injured in the Iraq/Kuwait/Afghanistan regions during Operation Iraqi Freedom and in Afghanistan during Operation Enduring Freedom and many of these isolates expressed a high degree of antimicrobial resistance. In addition, the incidence of multidrug-resistant (MDR) A. baumannii infections, associated with significant morbidity and mortality, are increasing worldwide. Thus there is a critical need to identify potential vaccine antigens and new drug targets expressed by A. baumannii. In the past year we have made significant progress in our research. We identified three surface polysaccharides and three proteins that may serve as vaccine candidates and/or drug targets. We have developed an animal model that will allow us to test the se bacterial components in vivo. Finally, we completely sequenced and annotated the genome of A. baumannii 307, which allows us to search for novel targets in silico.

Acinetobacter baumannii is a bacterial pathogen of increasing medical significance in military and civilian healthcare facilities. The importance of A. baumannii infections in war-related injuries is well established. A. baumannii was the most common gram-negative bacillus recovered from traumatic injuries to the lower extremities during the Vietnam War. More recently a new series of infections was reported in U.S. service personnel injured in the Iraq/Kuwait/Afghanistan regions during Operation Iraqi Freedom and in Afghanistan during Operation Enduring Freedom and many of these isolates expressed a high degree of antimicrobial resistance. In addition, the incidence of multidrug-resistant (MDR) A. baumannii infections, associated with significant morbidity and mortality, are increasing worldwide. Thus there is a critical need to identify potential vaccine antigens and new drug targets expressed by A. baumannii. In the past year we have made significant progress in our research. We identified three surface polysaccharides and three proteins that may serve as vaccine candidates and/or drug targets. We have developed an animal model that will allow us to test the se bacterial components in vivo. Finally, we completely sequenced and annotated the genome of A. baumannii 307, which allows us to search for novel targets in silico.

Acinetobacter baumannii is a bacterial pathogen of increasing medical significance in military and civilian healthcare facilities. The importance of A. baumannii infections in war-related injuries is well established. A. baumannii was the most common gram-negative bacillus recovered from traumatic injuries to the lower extremities during the Vietnam War. More recently a new series of infections was reported in U.S. service personnel injured in the Iraq/Kuwait/Afghanistan regions during Operation Iraqi Freedom and in Afghanistan during Operation Enduring Freedom and many of these isolates expressed a high degree of antimicrobial resistance. In addition, the incidence of multidrug-resistant (MDR) A. baumannii infections, associated with significant morbidity and mortality, are increasing worldwide. Thus there is a critical need to identify potential vaccine antigens and new drug targets expressed by A. baumannii. In the past year we have made significant progress in our research. We identified three surface polysaccharides and three proteins that may serve as vaccine candidates and/or drug targets. We have developed an animal model that will allow us to test the se bacterial components in vivo. Finally, we completely sequenced and annotated the genome of A. baumannii 307, which allows us to search for novel targets in silico.

Acinetobacter baumannii is a bacterial pathogen of increasing medical significance in military and civilian healthcare facilities. The importance of A. baumannii infections in war-related injuries is well established. A. baumannii was the most common gram-negative bacillus recovered from traumatic injuries to the lower extremities during the Vietnam War. More recently a new series of infections was reported in U.S. service personnel injured in the Iraq/Kuwait/Afghanistan regions during Operation Iraqi Freedom and in Afghanistan during Operation Enduring Freedom and many of these isolates expressed a high degree of antimicrobial resistance. In addition, the incidence of multidrug-resistant (MDR) A. baumannii infections, associated with significant morbidity and mortality, are increasing worldwide. Thus there is a critical need to identify potential vaccine antigens and new drug targets expressed by A. baumannii. In the past year we have made significant progress in our research. We identified three surface polysaccharides and three proteins that may serve as vaccine candidates and/or drug targets. We have developed an animal model that will allow us to test the se bacterial components in vivo. Finally, we completely sequenced and annotated the genome of A. baumannii 307, which allows us to search for novel targets in silico.

Tri 3 – 2018/2019

Trimester 2 2015/2016

One of the greatest benefits of escience—the use of distributed computing and data resources for scientific discovery—is the opportunity for scientists to begin working with data sets that would have been too large to work with otherwise and, consequently, ask questions that would have not been possible. There are many obvious challenges escience faces because of its distributed nature, but other challenges that, while not uniquely escientific, remain sufficiently domain-sensitive that solutions do not seem easily shareable. One particularly difficult problem is integration—how to coherently bring together disparate, massive data sets. Focus has been generally placed on the physical layer, borrowing from the three layers of data modeling, where details of implementation predominate. This problem will likely continue, though there is some hope leveraging “smart” architectures like smart clients. Logical integration—how to meaningfully bring together massive, disparate data sets—from the scientists’ perspective is even more challenging. Another challenge of escience is creating meaningful, interactive visualizations of massive data sets. A direct benefit of this kind of visualization is allowing the scientist to freely explore in a setting that is more familiar and intuitive. In this presentation will we discuss three ongoing projects, CATPA (Curation and Alignment Tool for Protein Analysis), INGeNE (Integrated, Gene Network Explorer), and SNPEx (SNP Explorer) that address the challenges of integration and visualization. CATPA is a smart client application that allows for the curation of protein families at the residue level, including deletions. Interaction is done visually. INGeNE is an application that allows for functional genomic discovery by building networks of relationships where an edge is a determined by a combination of microarray data, protein-protein data, gene-gene interaction data, and phenotypic expression data. SNPEx is an application that includes a novel algorithm to find the most informative set of tagging SNPs. Additionally, we decided to implement SNPEx in both Java/MySQL and C#/SQLServer 2000 to compare performance of the two systems and found the later to be superior in our suite of tests. ©2005 Microsoft Corporation. All rights reserved.

As a gynecological disease, endometriosis (EM) seriously endangers the health of women at the age of childbearing and is closely related to long noncoding RNAs (lncRNAs). Current studies have discovered that there are differential expressions of many kinds of lncRNAs in EM. However, whether lncRNAs can be applied as a new marker for the prediction of the recurrence of EM is still controversial. In this study, meta-analysis and bioinformatics analysis were carried out to explore the value of lncRNAs as a predictor of the recurrence of EM and to analyze its biological role.

In recent years, a variety of long noncoding RNA (lncRNA) has been confirmed to be involved in the initiation and progression of osteosarcoma. Taurine-up regulated gene 1 (TUG1) plays an important role in the formation, invasion and metastasis of osteosarcoma. Therefore, perhaps TUG1 is a potential biomarker for the prognosis of patients suffering from osteosarcoma. In this study, meta-analysis and bioinformatics were adopted to further explore the effects of TUG1 on the prognosis of patients with osteosarcoma and its potential molecular mechanism.

Its an archive of my neocities site

Its an archive of my neocities site