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6,363 results for “Mutations”
Figure 4 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)
Figure 4. High-resolution melting analysis (HRMA) for detection of mutation Trp-2027-Cys in Rottboellia cochinchinensis carboxyl-transferase domain of the acetyl-coenzyme A carboxylase gene conferring resistance to fluazifop-P-butyl. Three genotypes are included: wild type (homozygous TGG, susceptible), mutant homozygous (TGC, resistant), and artificial mutant heterozygous (TGG/TGC, possibly resistant). (A) Representative profiles of the melting curves (derivative melt curves), (B) normalized plot, and (C) difference plot using susceptible (wild type) as the reference genotype.
Fig. 1 in First report of kdr mutations in the voltage-gated sodium channel gene in the arbovirus vector, Aedes aegypti, from Nouakchott, Mauritania
Fig. 1 The combinations of kdr point mutations S989P, V1016G, and F1534C in adult female Aedes aegypti mosquitoes in Nouakchott, Mauritania
Figure 1 in Detection of the Trp-2027-Cys Mutation in Fluazifop-P-butyl-resistant Itchgrass (RottboelliO cochinchinensis) using High-Resolution Melting Analysis (HRMA)
Figure 1. Sequence alignment showing the single-nucleotide change (G/C) within the chloroplastic acetyl-coenzyme A carboxylase gene carboxyl-transferase domain fragments from Rottboellia cochinchinensis susceptible (G) and resistant (C) biotypes. The sequences of the HRMA primers are colored in red. Position numbers (Alopecurus myosuroides full ACCase sequence, GenBank AJ310767, numbering) are given above the nucleotide sequences. Conserved nucleotides are indicated by dots.
Tool Artifact for "Mutation-based Lifted Repair of Software Product Lines"
<p>In this work, we describe the installation, usage, and evaluation results of the tool SPLAllRepair introduced by the paper<br>``Mutation-based Lifted Repair of Software Product Lines''. We provide step-by-step instructions on how to download, run, and compare the tool's outputs to outputs described in the paper. The tool implements a novel lifted repair algorithm for program families (Software Product Lines - SPLs) based on code mutations. The inputs of our algorithm are an erroneous SPL and a specification given in the form of assertions. We use variability encoding to transform the given SPL into a single program, called family simulator, which is translated into a set of SMT formulas whose conjunction is satisfiable iff the simulator (i.e. the input SPL) violates an assertion. We use a predefined set of mutations applied to feature and program expressions of the given SPL.<br>The algorithm repeatedly mutates the erroneous family simulator and checks if it becomes (bounded) correct. The outputs are all minimal repairs in the form of minimal number of (feature and program) expression replacements such that the repaired SPL is (bounded) correct with respect to a given set of assertions. We present the experimental results showing that our approach is able to successfully repair various interesting #ifdef-based C SPLs.</p>
Drosophila serrata mutation accumulation lines: Phenotypic data on survival following infection with Drosophila C virus and reproduction
<p>The impact of selection on host immune function genes has been widely documented. However, it remains essentially unknown how mutation influences the quantitative immune traits that selection acts on. Applying a classical mutation accumulation (MA) experimental design in <em>Drosophila serrata</em>, we found the mutational variation in susceptibility (median time of death, LT50) to Drosophila C virus (DCV) was of similar magnitude to that reported for intrinsic survival traits. Mean LT50 did not change as mutations accumulated, suggesting no directional bias in mutational effects. Maintenance of genetic variance in immune function is hypothesised to be influenced by pleiotropic effects on immunity and other traits that contribute to fitness. To investigate this, we assayed female reproductive output for a subset of MA lines with relatively long or short survival times under DCV infection. Longer survival time tended to be associated with lower reproductive output, suggesting that mutations affecting susceptibility to DCV had pleiotropic effects on investment in reproductive fitness. Further studies are needed to uncover the general patterns of mutational effect on immune responses and other fitness traits, and to determine how selection might typically act on new mutations via their direct and pleiotropic effects.</p>
Mutation-guided Metamorphic Testing of Optimality in AI Planning
<p>Experimental results presented in the article <em>Mutation-guided Metamorphic Testing of Optimality in AI Planning</em>, both the figures and the raw data.</p> <p> </p> <p>The framework itself is hosted on GitHub (see the link below).</p> <p>In order to use the data with the framework, unzip the files of the archive <em>results.zip</em> inside the folder <em>results/</em>.</p>
Supplementary dataset for 'A randomised phase III trial of carboplatin compared with docetaxel in BRCA1/2 mutated and pre-specified triple negative breast cancer "BRCAness" subgroups: the TNT Trial'
<p>This dataset corresponds to the PAM50 gene expression profiling of primary tumour samples that were collected as part of the TNT clinical trial (ISRCTN97330959, NCT00532727, CRUK/07/012). NanoString® platform nCounter analysis was performed on the RNA extracts at the Institute of Cancer Research and Royal Marsden Hospital. The manuscript describing the trial outcome is currently under review in Nature Medicine.</p>
Using the Genetic Algorithm for the Optimization of Dynamic School Bus Routing Problem-Figure 6. Mutation process
<p>The individuals obtained at the end of crossing over might not provide the desired level of variability. In that case, the produced individuals are mutated independently from another individual in such a way that their own gene sequence will change. The mutation process is performed in the event that the mutation possibility that is specified in the beginning comes true. The results obtained from mutation can enhance the outcome or make it worse. It is of utmost importance to specify the most suitable mutation possibility. This possibility should be high enough to prevent the method from becoming stuck at a local point, but at the same time, low enough to allow the best results produced by crossing over and multiplexing. In this study, the mutation possibility was selected as 10%, and the locations of two randomly selected bus stops were changed during the mutation process. As in the crossing over, also during this process, the limitations regarding producing a new individual (route) were adapted. Figure 6 shows an example to mutation process.</p>
Structural modelling results to accompany the paper "Uncommon mutational profiles of metastatic colorectal cancer detected during routine genotyping using next generation sequencing: an update"
<p>This repository contains the results of modelling missense mutants in KRAS, NRAS and BRAF observed in our study in the corresponding protein structures. Modelling was performed using FoldX.</p>
Supplemental Data from: Association Between Mutation Clearance After Induction Therapy and Outcomes in Acute Myeloid Leukemia
<p>Supplemental Data for:</p> <p>Association Between Mutation Clearance After Induction Therapy and Outcomes in Acute Myeloid Leukemia. JAMA. 2015<br> (Paper available at: <a href="https://www.ncbi.nlm.nih.gov/pubmed/26305651">PubMed</a> <a href="https://jamanetwork.com/journals/jama/fullarticle/2429715">JAMA</a>)<br> <br> Authors: Jeffery M. Klco, M.D., Ph.D.* Christopher A. Miller, Ph.D.*, Malachi Griffith, Ph.D., Allegra Petti, Ph.D., David H. Spencer, M.D., Ph.D., Shamika Ketkar-Kulkarni, M.S., Lukas D. Wartman, M.D., Matthew Christopher, M.D., Ph.D., Tamara L. Lamprecht, B.S., Nicole M. Helton, B.S., Eric J. Duncavage, M.D., Jacqueline E. Payton, M.D., Ph.D., Jack Baty, B.A., Sharon E. Heath, Obi L. Griffith, Ph.D., Dong Shen, Ph.D., Jasreet Hundal, M.S., Gue Su Chang, Ph.D., Robert Fulton, M.S., Michelle O'Laughlin, B.S., Catrina Fronick, B.S., Vincent Magrini, Ph.D., Ryan T. Demeter, B.E., David E. Larson, Ph.D., Shashikant Kulkarni, M.S., Ph.D., Bradley A. Ozenberger, Ph.D., John S. Welch, M.D., Ph.D., Matthew J. Walter, M.D., Timothy A. Graubert, M.D., Peter Westervelt, M.D., Ph.D., Jerald P. Radich, M.D., Daniel C. Link, M.D., Elaine R. Mardis, Ph.D., John F. DiPersio, M.D., Ph.D., Richard K. Wilson, Ph.D., and Timothy J. Ley</p>
Classification of Gene Mutations and Cancer-Types with BioBombe Compressed Gene Expression Features
<p>BioBombe analysis applied to gene expression data from The Cancer Genome Atlas (TCGA) PanCanAtlas.</p> <p>Then, the compressed features learned through the serial compression are fed into several machine learning algorithms.</p> <p>The algorithms are used to predict mutation status (for the top 50 most mutated genes in TCGA) and cancer-type using the compressed gene expression features.</p> <p>Method and results described in https://github.com/greenelab/BioBombe. We use the classification approach outlined in https://github.com/greenelab/pancancer</p>
Synthetic mutational spectra with mixed and correlated mutational signatures SBS1 and SBS5
<p>Experience suggests that it harder to extract mutational signatures that always co-occur and that generate correlated numbers of mutations. Here we provide 12 data sets, each consisting of 500 synthetic mutational spectra with varying degrees of mixture and correlation between two mutational signatures. The signatures studied were SBS1, a "clock-like" signature due to deamination of 5-methyl cytosine that consists primarily of mutations from CG > TG, and SBS5, a relatively flat "clock-like" signature. By "clock-like" we mean that the numbers of mutations attributable to these signatures increase with patients' ages. The 12 data sets varied in two dimensions: (i) average ratio of the number of SBS1 to the number of SBS5 mutations in spectra in the data set and (ii) correlation between the number of SBS1 and the number of SBS5 mutations in spectra in the data set. The mutational signatures SBS1 and SBS5 are described at https://doi.org/10.7303/syn12025148 and https://doi.org/10.1101/322859. </p>
Supplementary data for: Detection of expressed mutations in acute myeloid leukemia cells using single cell RNA-sequencing
<p>Supplemental data for the publication:<br> Detection of expressed mutations in acute myeloid leukemia cells using single cell RNA-sequencing </p> <p>Contents: <br> - expression_matrices.tar - Gene/Barcode expression matrices from `cellranger count`<br> - *.seurat.rds - R object files with Seurat analyses and data structures for each sample<br> - scrna_mutations.tar.gz - copy of a git repository containing additional scripts and data - also hosted at <a href="https://github.com/genome/scrna_mutations">https://github.com/genome/scrna_mutations</a> (snapshot as of May 20, 2019)</p>
Antiviral activity of HIV-1 integrase strand-transfer inhibitors against mutants with integrase resistance-associated mutations and their frequency in treatment-naïve individuals
<p>The development of resistance to human immunodeficiency virus 1 (HIV-1) integrase strand-transfer inhibitors (INSTI) has been documented; however, knowledge of the impact of pre-existing integrase (IN) mutations on INSTI resistance (INSTI-R) is still evolving. The frequency of HIV-1 IN mutations in 2177 treatment-naïve subjects was investigated, along with the INSTI susceptibility of site-directed mutant viruses containing major and minor INSTI-R mutations. Total 6 of 39 minor INSTI-R mutations (M50I, S119P/G/T/R, and E157Q) were found in >1% of IN-treatment-naïve subjects with no impact on INSTI susceptibility. When each combined with major INSTI-R mutation, M50I, S119P, and E157Q led to decreased susceptibility to elvitegravir but remained sensitive to dolutegravir and bictegravir.</p>
Statistical Methods for Identifying Sequence Motifs Affecting Point Mutations
<p>Scripts and derived data for the indicated paper. Links to the <a href="https://zenodo.org/record/1204695">original data</a> and <a href="https://zenodo.org/record/3497585">library source code</a> used to generate this material. Inflate the ENU_mutation_classification.tar.gz archive, remove the ENU_mutation_classification/classifier directory (this will be replaced). Move all others archives into the ENU_mutation_classification directory and inflate them.</p>
Figure 1 in Genetic diversity and Kdr mutations of natural Aedes (Stegomyia) aegypti (Diptera: Culicidae) populations of Brazil
Figure 1 Distribution of the kdr alleles in Aedes aegypti populations for each Paraná locality. The state is detached, showing its multiple cities of collection.
Figure 3 in Genetic diversity and Kdr mutations of natural Aedes (Stegomyia) aegypti (Diptera: Culicidae) populations of Brazil
Figure 3 Dendrogram of the 40 haplotypes of Aedes aegypti divided into four groups. Neighbor-joining (NJ) tree of A. aegypti haplotypes using the Tamura-Nei parameter genetic distance model. Bootstrap values are marked under the respective nodes. S. albopictus was considered as external group. AS - Alvorada do Sul; MR - Marilena; MG -Maringá, NL - Nova Londrina; PV - Paranavaí; SC - São Carlos do Ivaí.
Figure 2 in Genetic diversity and Kdr mutations of natural Aedes (Stegomyia) aegypti (Diptera: Culicidae) populations of Brazil
Figure 2 Haplotype network of ND4 gene of Aedes aegypti populations of the six minicipalities of Paraná and others from America (Gonçalves da Silva et al., 2012). The mosquitoes referring to this analysis were renamed with PR next to the haplotype number (ex: H1PR), to differentiate from the haplotypes (H) found by Gonçalves da Silva et al. (2012). The rectangle represents the ancestral haplotype. The smaller circles connecting the identified haplotypes correspond to the non-sampled haplotypes (missing haplotypes) and classified as intermediaries.
Figure 3 in De novo mutations in the genome organizer CTCF cause intellectual disability
Figure 3. - Principal component analysis (PCA) of morphometric data. The ellipse highlights the group formed by the albino and normally pigmented specimens of the same size class. The albino is represented by the white square. Squares (N3 = 20-30 cm size-class); inverse triangles (N4 = 30-40 cm), circles (N5 = 40-50 cm), lozenges (N6 = 50-60 cm), and triangles (N7 = 60-70 cm).
Figure 2 in De novo mutations in the genome organizer CTCF cause intellectual disability
Figure 2. - Regressions of log of disc width vs. log of weight (A) and log of total length vs. log of weight (B) using the albino specimen and data from 28 female individuals of G. micrura. The albino specimen is represented by the white dot.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.