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Fig. 2 in Complete mitochondrial genome sequence of Bonasa sewerzowi (Galliformes: Phasianidae) and phylogenetic analysis
Fig. 2. The lrRNA secondary structure of Bonasa sewerzowi mitogenome and comparasion with B. bonasia. The different nucleotides in B.
Data and code for "Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR"
<p>This data set provides data files and R code to accompany the article <em>Differential methylation analysis of reduced representation bisulfite sequencing experiments using edgeR</em> published by F1000Research.</p> <p>The data consists of Reduced Representation BS-seq methylation profiles of epithelial populations from the mouse mammary gland, with n=2 biological replicates for each of three cell populations.</p> <p>RNA-seq expression profiles of luminal and basal mammary epithelial populations are also provided.</p> <p>The R code undertakes an differential methylation analysis of the BS-seq profiles and demonstrates a strong negative correlation between the differential methylation and differential expression results.</p>
Fig. 4 in MITOCHONDRIAL 16S AND 12S rRNA SEQUENCE ANALYSIS IN FOUR SALMONID SPECIES FROM ROMANIA
Fig. 4. Majority with bootstrap support consensus trees for combined data (16S rRNA and 12S rRNA). (a) Combined data Neighbor Joining tree, distance model Kimura 2 Parameters, transition/transversion ratio 2.3; (b) combined data Maximum Parsimony tree; (c) combined data Maxi-
Fig. 3. Majority with bootstrap support consensus trees for 12S in MITOCHONDRIAL 16S AND 12S rRNA SEQUENCE ANALYSIS IN FOUR SALMONID SPECIES FROM ROMANIA
Fig. 3. Majority with bootstrap support consensus trees for 12S rRNA. (a) 12S rRNA Maximum Parsimony tree; (b) 12S rRNA Neighbor Joining tree, distance model Kimura 2 Parameters, transi-
Fig. 2. Majority with bootstrap support consensus trees for 16S in MITOCHONDRIAL 16S AND 12S rRNA SEQUENCE ANALYSIS IN FOUR SALMONID SPECIES FROM ROMANIA
Fig. 2. Majority with bootstrap support consensus trees for 16S rRNA. (a) 16S rRNA Neighbor Joining tree, distance model Kimura 2 Parameters, transition/transversion ratio 2.3; (b) 16S rRNA Maximum Parsimony tree; (c) 16S rRNA Maximum Likelihood tree
Fig. 3. Phylogenetic trees from reported 18S in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig. 3. Phylogenetic trees from reported 18S rRNA genes of insects according to NJ. A. Based on sequences of full-length. B. Based on second conserved region.
Fig. 4 in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig. 4. Phylogenetic trees based on partial sequences from reported cox1 genes of insects according to NJ.
Fig.1 in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig.1. PCR result of 18S rRNA of Lymantria dispar. Separated bands (from left to right). 18S1, 18S2, 18S rRNA, DL2000 marker.
Fig. 7 in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 7. Nucleotide divergences of the cnidarians 18S and 28S rDNAs (datasets used in Table 1) based on corrected p-distances. Genetic distances between each paired sequence were calculated by the Kimura 2-parameter model, where a total of 16 cnidarian species were compared. Statistical analysis showed that the 18S rDNA divergences were significantly different from those of 28S rDNA (Student t-test, P <0.05, N = 66).
Fig. 6 in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 6. Phylogenetic relationships of the family Pelagiidae, including the genera Chrysaora, Pelagia and Sanderia, inferred from 18S rDNA (A), 28S rDNA (B) and morphological characters (C), which were redrawn from Fig. 95 in Morandini and Marques (2010). Phylogenetic trees of the rDNAs were constructed using the maximum-likelihood (ML) algorithms with the GTR+G model. A jellyfish Cyanea capillata (the family Cyaneidae) was used as the outgroup. Additional Bayesian trees generated similar branch patterns. The first and second numbers at the nodes display bootstrap proportions (BP) and posterior probabilities (PP) obtained in the ML and Bayesian analyses, respectively. Branch lengths are proportional to the scale given. Thick lines represent congruent branches between 18S and 28S, and morphological systematics.
Fig. 4. A in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 4. A dot matrix comparison of rDNA sequences between Chrysaora pacifica (KY 212123) and Aurelia coerulea (EU276014). Color scale bars represent consecutive sequence length of some regions detected similarly between the two sequence pairs. The open boxes in matrices indicate rDNA coding regions such as 18S, 5.8S, and 28S.
Fig. 2. A in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 2. A schematic representation of the single unit of rDNA (A), and GC content (%), nucleic acid distribution (% thymine), sequence complexity, and entropy (dS) in 100-bp windows across the entire rDNA nucleotides of Chrysaora pacifica (B). In the full rDNA (A), solid boxes indicate the ribosomal RNA genes and thin lines represent ITS or IGS. Nucleotide sequences in length and GC composition of each locus are represented near a line by calculation from a single unit of rDNA. The putative transcription start site is represented by an arrow; solid inverted-triangles represent sub-repeats in IGS.
Fig. 5. Phylogenetic relationships between jellyfishes within the order Semaeostomeae inferred from nearly complete 18S in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 5. Phylogenetic relationships between jellyfishes within the order Semaeostomeae inferred from nearly complete 18S rDNA (A) and partial 28S rDNA sequences (B) with maximum-likelihood (ML) algorithms. ML analyses of 18S and 28S were used as the nucleotide substitution model of GTR+G. Two hydrozoans (Hydractinia echinata and Podocoryne carnea for 18S rDNA; Astrohydra japonica and Melicertissa sp. for 28S) were included as the outgroups. Additional Bayesian analysis generated similar topology of the tree compared with the ML tree. Posterior probabilities (PP) from the analyses were incorporated into the ML tree to support the strength of each branch. The first and second numbers at the nodes display bootstrap proportions (BP) (> 50%) in ML and PP (> 0.50) in Bayesian, respectively. Branch lengths are proportional to the scale given. *Represents controversial species names, because they were suspected as different species by Bayha et al. (2017).
Fig. 1 in Comprehensive Analysis of the Jellyfish (Goette, 1886) (Semaeostomeae: Pelagiidae) with Description of the Complete rDNA Sequence.
Fig. 1. Live Chrysaora pacifica in natural habitat: basolateral (A and B), lateral (C) and apical view (D).
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019) in Variability of the gene cyt b in the Korean field mouse Apodemus peninsulae Thomas, 1906 - a reservoir host of AMRV in the Khasansky District of Primorsky Krai
Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019)
Sample datasets for Transposon insertion sequencing analysis tutorial
<p>The dataset contains five files:</p> <ol> <li>Tnseq-Tutorial-reads.fastqsanger.gz - A subset of TnSeq reads published in `Santiago, M., Matano, L. M., Moussa, S. H., Gilmore, M. S., Walker, S., & Meredith, T. C. (2015). A new platform for ultra-high density Staphylococcus aureus transposon libraries. <em>BMC Genomics</em>, <em>16</em>(1), 1–18. http://doi.org/10.1186/s12864-015-1361-3`</li> <li>condition_barcodes.fasta - Set of barcodes to separate reads from different experimental conditions</li> <li>construct_barcodes.fasta - Set of barcodes to separate reads from different transposon constructs</li> <li>staph_aur.fasta : Genome file for <em>Staphylococcus aureus </em></li> <li>staph_aur.fasta : Annotation file for <em>Staphylococcus aureus </em></li> </ol>
Bayesian network analysis of plasma microRNA sequencing data in patients with venous thrombosis
<p>This dataset contains the results of 2 related analyses, described in "Bayesian network analysis of plasma microRNA sequencing data in patients with venous thrombosis" (European Heart Journal Supplements, OUP). Link to the article: https://www.hal.inserm.fr/inserm-02310241</p> <p>1) In the directory "miRNAs_MARTHA_GWAS" : GWAS summary statistics for 162 circulating miRNAs in 344 VTE patients from the MARTHA cohort.</p> <p>Header for each summary file:</p> <p>Trait: miRNA id<br> chr: Chromosome<br> pos.hg19: Position of the variant in hg19/GRCh37 coordinates<br> SNP: rsid<br> A1: Reference allele on the forward strand<br> A2: Alternate allele on the forward strand<br> freq_A1: Frequency of reference allele<br> rsqr: Imputation quality defined by MACH<br> beta_A1: Estimated effect size (beta regression coefficient) of reference allele<br> se_A1: Estimated standard error of beta<br> p: p-value (significance of estimated beta)<br> z.score: Z-score</p> <p> </p> <p>2) In the directory "meta_analysis": Random effect meta-analysis combining the results of our GWAS on the MARTHA cohort, and the results from a similar analysis conducted by Nikpay et al. (doi: 10.1093/cvr/cvz030). Summary statistics of 142 microRNAs, common to both datasets, were processed (and combine 1054 samples).</p> <p>Header for each summary file:</p> <p>chr: Chromosome<br> pos.hg19: Position of the variant in hg19/GRCh37 coordinates<br> SNP: rsid<br> A1: Reference allele on the forward strand<br> A2: Alternate allele on the forward strand<br> N: Sample size<br> Q: Cochran's heterogeneity statistic<br> Q.p: p-value of Cochran's Q<br> beta_A1: Estimated effect size (beta regression coefficient) of reference allele<br> se_A1: Estimated standard error of beta<br> p: p-value (significance of estimated beta)</p> <p> </p>
Figure 3 in Analysis of mitochondrial cytochrome b gene sequences of marine leech, Pterobdella arugamensis
Figure 3. Haplotype network of P. arugamensis CYTB gene sequences. Different colours represent different locations. The circle size is proportional to the sample number. Each dash on the line symbolises one mutational event. Tiny white circle indicates median vector.
Figure 2 in Analysis of mitochondrial cytochrome b gene sequences of marine leech, Pterobdella arugamensis
Figure 2. Representative maximum-likelihood tree showing nine haplotypes of P. arugamensis based on CYTB gene sequences. Ozobranchus jantseanus and Erpobdella japonica from the GenBank database were used as outgroups. The bootstrap percentages (1000 replicates) for maximum likelihood/maximum parsimony/neighbour joining trees are shown.
Figure 1 in Analysis of mitochondrial cytochrome b gene sequences of marine leech, Pterobdella arugamensis
Figure 1. Locations of P. arugamensis used in this study. Sampling locations are shown by blue circles: Brunei (TP: Tanjong Pelumpong, PK: Pulau Kaingaran), Surabaya in Indonesia (EJ), and Lombok in Indonesia (EL). Red circle indicates the GenBank sample from Hainan, China. The map was adapted from the USGS National Map Viewer (open access) at http://viewer.nationalmap.gov/viewer/.
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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.