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261 results for “Mus”
SiSEC18-MUS 7s Excerpts
<p>This dataset contains 7s excerpts from the Signal Separation Evaluation Campaign (SiSEC 2018). It accompanies the objective scores as submitted via the <a href="https://github.com/sigsep/sigsep-mus-2018">official github repository. </a>The excerpts were generated using a method as described<a href="https://github.com/sigsep/sigsep-mus-cutlist-generator"> here</a> that selects 7 seconds from each audio track by determining the most active parts of each source.</p>
Genome indexes for Mus musculus (mm39)
<p><strong>BUILDING HISAT2 INDEXES IN CSC</strong><br> Here is the case for house mouse genome (mm39). The genome indexing step requires big memory and it might not be possible to carry out it on a laptop. Genome indexes for Mus musculus (mm39) were created using HISAT2 v2.2.1 on CSC (IT Center for Science), thanks to CSC-Puhti. </p> <p><strong>1. Create conda environment folder file to install the required packages, install and add the bin directory to the path.</strong><br> mkdir STRTN-env<br> conda-containerize new --prefix STRTN-env STRTN-env.yml<br> export PATH="<install_dir>/STRTN-env/bin:$PATH"</p> <p><strong>2. Load the required module.</strong><br> module load tykky<br> export PATH="<install_dir>/STRTN-env/bin:$PATH"<br> module load r-env<br> if test -f ~/.Renviron; then<br> sed -i '/TMPDIR/d' ~/.Renviron<br> fi<br> echo "TMPDIR=${WorkingDir_PATH}" >> ~/.Renviron<br> <br> <strong>3. Obtain the genome sequences of reference and ERCC spike-ins.</strong> <strong><em>You may add the ribosomal DNA repetitive unit for human (U13369) and mouse (BK000964).</em></strong><br> wget https://hgdownload.soe.ucsc.edu/goldenPath/mm39/bigZips/mm39.fa.gz<br> unpigz -c mm39.fa.gz | ruby -ne '$ok = $_ !~ /^>chrUn_/ if $_ =~ /^>/; puts $_ if $ok' > mouse_reference.fasta<br> wget https://tsapps.nist.gov/srmext/certificates/documents/SRM2374_putative_T7_products_NoPolyA_v2.FASTA<br> cat SRM2374_putative_T7_products_NoPolyA_v2.FASTA >> mouse_reference.fasta</p> <p><strong>4. Extract splice sites and exons from a GTF file.<em> Here we used wgEncodeGencodeBasicVM30 as the annotation file. You may additionally perform `hisat2_extract_snps_haplotypes_UCSC.py` to extract SNPs and haplotypes from a dbSNP file for human and mouse.</em></strong><br> wget https://hgdownload.soe.ucsc.edu/goldenPath/mm39/database/wgEncodeGencodeBasicVM30.txt.gz<br> unpigz -c wgEncodeGencodeBasicVM30.txt.gz | hisat2_extract_splice_sites.py - | grep -v ^chrUn > splice_sites.txt<br> unpigz -c wgEncodeGencodeBasicVM30.txt.gz | hisat2_extract_exons.py - | grep -v ^chrUn > exons.txt<br> <br> <strong>5. Build the HISAT2 index<em>. This outputs a set of files with suffixes. Here, `mouse_reference.1.ht2`, `mouse_reference.2.ht2`, ..., `mouse_reference.8.ht2` are generated.<br>In this case, `mouse_reference` is the basename used for `-i, --index`.</em></strong><br> hisat2-build mouse_reference.fasta --ss splice_sites.txt --exon exons.txt mouse_index/mouse_reference</p> <p><strong>6. Create the sequence dictionary for the reference and Spike-in sequences.<em> This is required for the Picard</em></strong> MergeBamAlignment program. Note that the original FASTA file (`mouse_reference.fasta` here) is also required.<br> picard CreateSequenceDictionary R=mouse_reference.fasta O=mouse_reference.dict<br> <br> <strong>7. Put the genome indexes, genome fasta file, sequence dictionary to same folder.</strong><br> mv mouse_reference.dict mouse_reference<br> mv mouse_reference.fasta mouse_reference</p>
Image 1 in Parasitic associations of a threatened Sri Lankan rainforest rodent, Mus mayori pococki (Rodentia: Muridae)
Image 1. Photomicrographs of the intestinal parasitic eggs & the larva detected in faecal samples of Mus mayori.
Fig. 5. The marginal response curve for the explanatory variable Bio14 in Modelling The Bioclimatic Niche And Distribution Of The Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), In Ukraine
Fig. 5. The marginal response curve for the explanatory variable Bio14 (Precipitation of driest week). (HS — habitat suitability).
Fig. 1 in Modelling The Bioclimatic Niche And Distribution Of The Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), In Ukraine
Fig. 1. Occurrences of Mus spicilegus in Ukraine and neighbouring areas used for creating the ENM. [Data collected before (triangles) and after (circles) 1990.]
Fig. 4. The marginal response curve for the explanatory variable Bio09 in Modelling The Bioclimatic Niche And Distribution Of The Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), In Ukraine
Fig. 4. The marginal response curve for the explanatory variable Bio09 (Mean temperature of driest quarter). (HS — habitat suitability).
Fig. 7. 0.5 in Modelling The Bioclimatic Niche And Distribution Of The Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), In Ukraine
Fig. 7. 0.5 oC isotherms for Bio09 (Mean temperature of driest quarter) for different time periods: 1 — 1980s; 2 — 2000s; 3 — contemporary; 4 — predicted for 2030.
Fig. 6. A in Modelling The Bioclimatic Niche And Distribution Of The Steppe Mouse, Mus Spicilegus (Rodentia, Muridae), In Ukraine
Fig. 6. A current climate habitat suitability map for the Steppe mouse (Mus spicilegus) in Ukraine. Darker shades of gray denote areas of higher predicted habitat suitability probabilities (≥ 0.5) and lighter shades correspond to lower (≥ 0.311 and <0.5). [Administrative regions in Ukraine: 1 — Chernihiv Region; 2 — Kyiv Region; 3 — Ternopil Region; 4 — Ivano-Frankivsk Region.]
Genotypic sex shapes maternal care in the African Pygmy mouse, Mus minutoides
<p><span>Sexually dimorphic behaviours, such as parental care, have long been thought to be </span><span>mainly</span><span> driven by gonadal hormones. In the past two decades, a few studies have challenged this view, highlighting the direct influence of the sex chromosome complement (XX vs XY or ZZ vs ZW). The African pygmy mouse, </span><span>Mus minutoides</span><span>, is a wild mouse species with naturally occurring XY sex reversal induced by a third, feminizing X* chromosome, leading to three female genotypes: XX, XX* and X*Y. Here, we show that sex reversal in X*Y females shapes a divergent maternal care strategy (maternal aggression, pup retrieval and nesting behaviours) from both XX and XX* females. Although neuroanatomical investigations were inconclusive, we show that the dopaminergic system in the anteroventral periventricular nucleus of the hypothalamus is worth investigating further as it may support differences in pup retrieval behaviour between females. Combining </span><span>behaviours</span><span> and neurobiology in a rodent subject to natural selection, we evaluate potential candidates for the neural basis of maternal behaviours and strengthen the underestimated role of the sex chromosomes in shaping sex differences in brain and behaviours. All things considered, we further highlight the emergence of a third sexual phenotype, challenging the binary view of phenotypic sexes.</span></p>
Plate III. Tyrannosaurus rex. Section of skull showing brain cavity. Amer. Mus. No. 5029: Scale 1/2. in Crania of Tyrannosaurus and Allosaurus
Plate III. Tyrannosaurus rex. Section of skull showing brain cavity. Amer. Mus. No. 5029: Scale 1/2.
Fig. 5 in Distinguishing Mus Spicilegus From Mus Musculus (Rodentia, Muridae) By Using Cranial Measurements
Fig. 5. The hyperbolic regression of coefficient of variation (CV) on mean (X). The regression of the joint exponential grow curve: r = 0.86 (proportion of variance accounted for: 0.73).
Fig 2 in Sexual Size Dimorphism In Free-Living Populations Of Mus Musculus: Are Male House Mice Bigger?
Fig 2. Variation in SSD during the first five weeks of postnatal development in five mice populations. SSD is expressed as Lowich-Gibbons ratios of mean body weight (see under Material and Methods)
Fig. 1 in Sexual Size Dimorphism In Free-Living Populations Of Mus Musculus: Are Male House Mice Bigger?
Fig. 1. Map of the studied localities: 1 = Czech Republic, 2 = The Balkans, 3 = Iran, 4 = Jordan, 5 = hybrids. See Material and Methods for coordinates of the localities
Fig. 2. A in First record of Trypanosoma infection in Mediterranean mouse (Mus macedonicus Petrov & Ružić, 1983) in Bulgaria
Fig. 2. A blood smear showing trypanosomes (white arrows) stained with acridine orange. Parasites (orange) are easily recognizable alongside red blood cells (mature – dark green; young – red) (magnification 400x).
Fig. 1 in First record of Trypanosoma infection in Mediterranean mouse (Mus macedonicus Petrov & Ružić, 1983) in Bulgaria
Fig. 1. Location of the study area with investigated sites of Trypanosoma infection – site 1 (N42°3ʹ58.68ʺ; E24°49ʹ18.57ʺ) and site 2 (N42°3ʹ13.49ʺ; E24°49ʹ39.89ʺ).
Fig. 3 in First record of Trypanosoma infection in Mediterranean mouse (Mus macedonicus Petrov & Ružić, 1983) in Bulgaria
Fig. 3. Microphotograph of Trypanosoma musculi from Mus macedonicus near Plovdiv in a thin blood smear (magnification 1000x).
Fig. 3 in Peroral Echinococcus multilocularis egg inoculation in Myodes glareolus, Mesocricetus auratus and Mus musculus (CD-1 IGS and C57BL/6j)
Fig. 3. Number of metacestodes of varying sizes in individual species at 6 wpi (M. glareolus at 8 wpi) after receiving 100 viable E. multilocularis eggs. A <1 mm, B 1 - Ý2 mm, C> 2 - Ý3 mm, D> 3 - Ý4 mm, E 4 - Ý5 mm, F> 5 mm. Data from current study and (Woolsey et al., 2015a; Woolsey et al., 2015b).
Fig. 2 in Peroral Echinococcus multilocularis egg inoculation in Myodes glareolus, Mesocricetus auratus and Mus musculus (CD-1 IGS and C57BL/6j)
Fig. 2. Mean establishment of E. multilocularis oncospheres in the different rodent intermediate hosts after receiving 100 viable eggs at 6 wpi (M. glareolus at 8 wpi). Data from current study and (Woolsey et al., 2015a; Woolsey et al., 2015b).
SiSEC18-MUS 30s Excerpts
<p>This dataset contains 30s excerpts from the Signal Separation Evaluation Campaign (SiSEC 2018). It accompanies the objective scores as submitted via the <a href="https://github.com/sigsep/sigsep-mus-2018">official github repository. </a>The excerpts were generated using a method as described<a href="https://github.com/sigsep/sigsep-mus-cutlist-generator"> here</a> that selects 30 seconds from each audio track by determining the most active parts of each source.</p>
MinION 1D² Reads From Mus musculus GL261 Cell Lines
<p>Called FASTQ and raw FAST5 MinION cDNA reads (1D²) from a murine GL261 neuroblastoma cell line, cultured at the Malaghan Institute of Medical Research, sequenced on a R9.5 flow cell in August 2017 using the LSK309 1D² kit for ligating ONT adapters to cDNA generated using strand-switching primers.</p> <p>The called reads for the entire sequencing run are available:</p> <ul> <li>called_reads_1Dsq_Olivier_GL261_cDNA_2017-Aug-04.tar.gz -- called reads from both/all runs (1D²-corrected fastq files only).</li> <li>called_reads_uncorrected_Olivier_GL261_cDNA_2017-Aug-04.tar.gz -- uncorrected reads from both/all runs.</li> <li>metadata_called_reads_Olivier_GL261_cDNA_2017-Aug-04.tar.gz -- metadata associated with all called sequences (e.g. sequencing_summary.txt)</li> </ul> <p>This dataset only includes a subset of the total reads as raw signal / FAST5 files:</p> <ul> <li>Actb_GL261_cDNA_2017-Aug-04_1D2.tar -- reads from one run that mapped (in whole or in part) to a mouse beta-actin transcript [<a href="http://asia.ensembl.org/Mus_musculus/Transcript/Summary?db=core;g=ENSMUSG00000029580;r=5:142903234-142903654;t=ENSMUST00000100497">ENSMUST00000100497.10</a>].</li> <li>Ubb_GL261_cDNA_2017-Aug-04_1D2.tar -- reads from one run that mapped (in whole or in part) to a mouse ubiquitin transcript [<a href="http://asia.ensembl.org/Mus_musculus/Transcript/Summary?db=core;g=ENSMUSG00000019505;r=11:62551171-62553213;t=ENSMUST00000019649">ENSMUST00000019649.3</a>].</li> </ul>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.