Source Code for Biology and Medicine最新文献

Background: Malaria has been a major life threatening mosquito borne disease from long since. Unavailability of any effective vaccine and recent emergence of multi drug resistant strains of malaria pathogen Plasmodium falciparum continues to cause persistent deaths in the tropical and sub-tropical region. As a result, demands for new targets for more effective anti-malarial drugs are escalating. Transketolase is an enzyme of the pentose phosphate pathway; a novel pathway which is involved in energy generation and nucleic acid synthesis. Moreover, significant difference in homology between Plasmodium falciparum transketolase (Pftk) and human (Homo sapiens) transketolase makes it a suitable candidate for drug therapy. Our present study is aimed to predict the 3D structure of Plasmodium falciparum transketolase and design an inhibitor against it.

Results: The primary and secondary structural features of the protein is calculated by ProtParam and SOPMA respectively which revealed the protein is composed of 43.3 % alpha helix and 33.04 % random coils along with 15.62 % extended strands, 8.04 % beta turns. The three dimensional structure of the transketolase is constructed using homology modeling tool MODELLAR utilizing several available transketolase structures as templates. The structure is then subjected to deep optimization and validated by structure validation tools PROCHECK, VERIFY 3D, ERRAT, QMEAN. The predicted model scored 0.74 for global model reliability in PROCHECK analysis, which ensures the quality of the model. According to VERIFY 3D the predicted model scored 0.77 which determines good environmental profile along with ERRAT score of 78.313 which is below 95 % rejection limit. Protein-protein and residue-residue interaction networks are generated by STRING and RING server respectively. CASTp server was used to analyze active sites and His 109, Asn 108 and His 515 are found to be more positive site to dock the substrate, in addition molecular docking simulation with Autodock vina determined the estimated free energy of molecular binding was of -6.6 kcal/mol for most favorable binding of 6'-Methyl-Thiamin Diphosphate.

Conclusion: This predicted structure of Pftk will serve first hand in the future development of effective Pftk inhibitors with potential anti-malarial activity. However, this is a preliminary study of designing an inhibitor against Plasmodium falciparum 3D7; the results await justification by in vitro and in vivo experimentations.

Background: Sequencing and genotyping technology advancements have led to massive, growing repositories of spatially explicit genetic data and increasing quantities of temporal data (i.e., ancient DNA). These data will allow more complex and fine-scale inferences about population history than ever before; however, new methods are needed to test complex hypotheses.

Results: This article presents popRange, a forward genetic simulator, which incorporates large-scale genetic data with stochastic spatially and temporally explicit demographic and selective models. Features such as spatially and temporally variable selection coefficients and demography are incorporated in a highly flexible manner. popRange is implemented as an R package and presented with an example simulation exploring a selected allele's trajectory in multiple subpopulations.

Conclusions: popRange allows researchers to evaluate and test complex scenarios by simulating large-scale data with complicated demographic and selective features. popRange is available for download at http://cran.r-project.org/web/packages/popRange/index.html.

Background: High-throughput transcriptional profiling using Next-Generation Sequencing (RNA-Seq) or microarray technology have become standard tools in molecular biology. Successful investigations of gene regulatory mechanisms from these data typically employ mathematical models of biological networks.

Results: We have developed Wormpath, a software for molecular network discovery which operates on the genetic and physical interaction data of the Wormbase, a comprehensive resource of molecular data on Caenorhabditis elegans. We use Wormpath to show that the insulin/insulin-like growth factor signalling (IIS) pathway responds to UV-induced DNA damage during development.

Conclusions: Our software provides highly facilitated access to C. elegans interaction data and is capable of identifying essential molecular networks within a list of differentially expressed genes.

Background: MicroRNA expression can be quantified using sequencing techniques or commercial microRNA-expression arrays. Recently, the AgiMicroRna R-package was published that enabled systematic preprocessing and statistical analysis for Agilent microRNA arrays. Here we describe MagiCMicroRna, which is a user-friendly web interface for this package, together with a new filtering approach.

Results: We used MagiCMicroRna to normalize and filter an Agilent miRNA microarray dataset of cancerous and normal tissues from 14 different patients. With the standard filtering procedure, 250 out of 817 microRNAs remained, whereas the new group-specific filtering approach resulted in broader datasets for further analysis in most groups (>279 microRNAs remaining).

Conclusions: The user-friendly web interface of MagiCMicroRna enables researchers to normalize and filter Agilent microarrays by the click of one button. Furthermore, MagiCMicroRna provides flexibility in choosing the filtering method. The new group-specific filtering approach lead to an increased number and additional tissue-specific microRNAs remaining for subsequent analysis compared to the standard procedure. The MagiCMicroRna web interface and source code can be downloaded from https://bitbucket.org/mutgx/magicmicrorna.git.

Background: The study of biological membranes using Molecular Dynamics has become an increasingly popular means by which to investigate the interactions of proteins, peptides and potentials with lipid bilayers. These interactions often result in changes to the properties of the lipids which can modify the behaviour of the membrane. Membrainy is a unified membrane analysis tool that contains a broad spectrum of analytical techniques to enable: measurement of acyl chain order parameters; presentation of 2D surface and thickness maps; determination of lateral and axial headgroup orientations; measurement of bilayer and leaflet thickness; analysis of the annular shell surrounding membrane-embedded objects; quantification of gel percentage; time evolution of the transmembrane voltage; area per lipid calculations; and quantification of lipid mixing/demixing entropy.

Results: Each analytical component within Membrainy has been tested on a variety of lipid bilayer systems and was found to be either comparable to or an improvement upon existing software. For the analytical techniques that have no direct comparable software, our results were confirmed with experimental data.

Conclusions: Membrainy is a user-friendly, intelligent membrane analysis tool that automatically interprets a variety of input formats and force fields, is compatible with both single and double bilayers, and capable of handling asymmetric bilayers and lipid flip-flopping. Membrainy has been designed for ease of use, requiring no installation or configuration and minimal user-input to operate.

Motivation: Correctly modeling population structure is important for understanding recent evolution and for association studies in humans. While pre-existing knowledge of population history can be used to specify expected levels of subdivision, objective metrics to detect population structure are important and may even be preferable for identifying groups in some situations. One such metric for genomic scale data is implemented in the cross-validation procedure of the program ADMIXTURE, but it has not been evaluated on recently diverged and potentially cryptic levels of population structure. Here, I develop a new method, AdmixKJump, and test both metrics under this scenario.

Findings: I show that AdmixKJump is more sensitive to recent population divisions compared to the cross-validation metric using both realistic simulations, as well as 1000 Genomes Project European genomic data. With two populations of 50 individuals each, AdmixKJump is able to detect two populations with 100% accuracy that split at least 10KYA, whereas cross-validation obtains this 100% level at 14KYA. I also show that AdmixKJump is more accurate with fewer samples per population. Furthermore, in contrast to the cross-validation approach, AdmixKJump is able to detect the population split between the Finnish and Tuscan populations of the 1000 Genomes Project.

Conclusion: AdmixKJump has more power to detect the number of populations in a cohort of samples with smaller sample sizes and shorter divergence times.

Availability: A java implementation can be found at https://sites.google.com/site/igsevolgenomicslab/home/downloads.

Background: Genome-wide association studies (GWAS) are an important tool for the mapping of complex traits and diseases. Visual inspection of genomic annotations may be used to generate insights into the biological mechanisms underlying GWAS-identified loci.

Results: We developed LocusTrack, a web-based application that annotates and creates plots of regional GWAS results and incorporates user-specified tracks that display annotations such as linkage disequilibrium (LD), phylogenetic conservation, chromatin state, and other genomic and regulatory elements. Currently, LocusTrack can integrate annotation tracks from the UCSC genome-browser as well as from any tracks provided by the user.

Conclusion: LocusTrack is an easy-to-use application and can be accessed at the following URL: http://gump.qimr.edu.au/general/gabrieC/LocusTrack/. Users can upload and manage GWAS results and select from and/or provide annotation tracks using simple and intuitive menus. LocusTrack scripts and associated data can be downloaded from the website and run locally.

Background: The graphical visualization of gene expression data using heatmaps has become an integral component of modern-day medical research. Heatmaps are used extensively to plot quantitative differences in gene expression levels, such as those measured with RNAseq and microarray experiments, to provide qualitative large-scale views of the transcriptonomic landscape. Creating high-quality heatmaps is a computationally intensive task, often requiring considerable programming experience, particularly for customizing features to a specific dataset at hand.

Methods: Software to create publication-quality heatmaps is developed with the R programming language, C++ programming language, and OpenGL application programming interface (API) to create industry-grade high performance graphics.

Results: We create a graphical user interface (GUI) software package called HeatmapGenerator for Windows OS and Mac OS X as an intuitive, user-friendly alternative to researchers with minimal prior coding experience to allow them to create publication-quality heatmaps using R graphics without sacrificing their desired level of customization. The simplicity of HeatmapGenerator is that it only requires the user to upload a preformatted input file and download the publicly available R software language, among a few other operating system-specific requirements. Advanced features such as color, text labels, scaling, legend construction, and even database storage can be easily customized with no prior programming knowledge.

Conclusion: We provide an intuitive and user-friendly software package, HeatmapGenerator, to create high-quality, customizable heatmaps generated using the high-resolution color graphics capabilities of R. The software is available for Microsoft Windows and Apple Mac OS X. HeatmapGenerator is released under the GNU General Public License and publicly available at: http://sourceforge.net/projects/heatmapgenerator/. The Mac OS X direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_MAC_OSX.tar.gz/download. The Windows OS direct download is available at: http://sourceforge.net/projects/heatmapgenerator/files/HeatmapGenerator_WINDOWS.zip/download.

[This corrects the article DOI: 10.1186/1751-0473-9-9.].

Background: Eelgrass is a cosmopolitan seagrass species that provides important ecological services in coastal and near-shore environments. Despite its relevance, loss of eelgrass habitats is noted worldwide. Restoration by replanting plays an important role, and accurate measurements of the standing crop and productivity of transplants are important for evaluating restoration of the ecological functions of natural populations. Traditional assessments are destructive, and although they do not harm natural populations, in transplants the destruction of shoots might cause undesirable alterations. Non-destructive assessments of the aforementioned variables are obtained through allometric proxies expressed in terms of measurements of the lengths or areas of leaves. Digital imagery could produce measurements of leaf attributes without the removal of shoots, but sediment attachments, damage infringed by drag forces or humidity contents induce noise-effects, reducing precision. Available techniques for dealing with noise caused by humidity contents on leaves use the concepts of adjacency, vicinity, connectivity and tolerance of similarity between pixels. Selection of an interval of tolerance of similarity for efficient measurements requires extended computational routines with tied statistical inferences making concomitant tasks complicated and time consuming. The present approach proposes a simplified and cost-effective alternative, and also a general tool aimed to deal with any sort of noise modifying eelgrass leaves images. Moreover, this selection criterion relies only on a single statistics; the calculation of the maximum value of the Concordance Correlation Coefficient for reproducibility of observed areas of leaves through proxies obtained from digital images.

Results: Available data reveals that the present method delivers simplified, consistent estimations of areas of eelgrass leaves taken from noisy digital images. Moreover, the proposed procedure is robust because both the optimal interval of tolerance of similarity and the reproducibility of observed leaf areas through digital image surrogates were independent of sample size.

Conclusion: The present method provides simplified, unbiased and non-destructive measurements of eelgrass leaf area. These measurements, in conjunction with allometric methods, can predict the dynamics of eelgrass biomass and leaf growth through indirect techniques, reducing the destructive effect of sampling, fundamental to the evaluation of eelgrass restoration projects thereby contributing to the conservation of this important seagrass species.