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485 results for “pathway analysis”
Data and analysis of proteomic responses to hexokinase-II depletion in GAL80 and gal80Δ Saccharomyces cerevisiae with an engineered sesquiterpene-pathway
<p>Dataset 1: <a href="https://zenodo.org/api/files/ece3309f-0ca2-4773-b2e3-b1c5c839faa4/GAL80_HXK2_Vs._dhxk2p_20200324_T2_004.xlsx">GAL80_HXK2_Vs._dhxk2p_20200324_T2_004.xlsx</a></p> <p>The comparison between strain ILHA o128R+pJT9RFR (dHxk2p) and ILHA o401R+ pJT9RFR (HXK2) under the conditions with the addition of 1-Naphthaleneacetic acid and in the exponential growth phase and the ethanol growth phase. </p> <p> </p> <p>Dataset 2: <a href="https://zenodo.org/api/files/ece3309f-0ca2-4773-b2e3-b1c5c839faa4/gal80%CE%94_HXK2_Vs._dhxk2p_20200219_T1_004.xlsx">gal80Δ_HXK2_Vs._dhxk2p_20200219_T1_004.xlsx</a></p> <p>The comparison between strain ILHA NLD128-1 (dHxk2p) and ILHA NLD401 (HXK2) under the conditions with the addition of 1-Naphthaleneacetic acid and in the exponential growth phase (EXP) and the ethanol growth phase (ETH). </p> <p> </p>
Numerical Output for Analysis of Atlantic Water Pathways in Fram Strait
<p>This dataset contains data for the publication: Shifts of the Recirculation Pathways in central Fram Strait drive Atlantic Intermediate Water Variability on Northeast Greenland shelf (McPherson et al., JGR Oceans).</p>
Single-molecule analysis of the entire perfringolysin O pore formation pathway
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The results of RNA seq analysis: Curcumin promotes progression of AApoAII amyloidosis and peroxisome proliferation in mice by activating the PPARα signaling pathway
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Chemical informatics combined with Kendrick mass analysis to enhance annotation and identify pathways in soybean metabolomics
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Data from: Comparative genomic analysis of nine Sphingobium strains: insights into their evolution and Hexachlorocyclohexane (HCH) degradation pathways
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Genomics of new ciliate lineages provides insight into the evolution of obligate anaerobiosis - single gene datasets for phylogenomic analysis of anaerobic ciliates (SAL, Ciliophora), protein datasets for mitochondrial pathways prediction, and mitochondrial genomes
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Pan-cancer Aberrant Pathway Activity Analysis (PAPAA)
<p>Information about the dataset files:</p> <p>1) pancan_rnaseq_freeze.tsv.gz: Publicly available gene expression data for the TCGA Pan-cancer dataset. File: PanCanAtlas EBPlusPlusAdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.tsv was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/3586c0da-64d0-4b74-a449-5ff4d9136611] [<a href="https://doi.org/10.1016/j.celrep.2018.03.046">https://doi.org/10.1016/j.celrep.2018.03.046</a>]</p> <p>2) pancan_mutation_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset. File: mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046] </p> <p>3) pancan_GISTIC_threshold.tsv.gz: Publicly available Gene- level copy number information of the TCGA Pan-cancer dataset. This file is processed using script process_copynumber.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. The files copy_number_loss_status.tsv.gz and copy_number_gain_status.tsv.gz generated from this data are used as inputs in our Galaxy pipeline. [https://xenabrowser.net/datapages/?cohort=TCGA%20Pan-Cancer%20(PANCAN)&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443] [<a href="https://doi.org/10.1016/j.celrep.2018.03.046">https://doi.org/10.1016/j.celrep.2018.03.046</a>]</p> <p>4) mutation_burden_freeze.tsv.gz: Publicly available Mutational information for TCGA Pan-cancer dataset mc3.v0.2.8.PUBLIC.maf.gz was processed using script process_sample_freeze.py by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/][http://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc] [https://doi.org/10.1016/j.celrep.2018.03.046]</p> <p>5) sample_freeze.tsv or sample_freeze_version4_modify.tsv: The file lists the frozen samples as determined by TCGA PanCancer Atlas consortium along with raw RNAseq and mutation data. These were previously determined and included for all downstream analysis All other datasets were processed and subset according to the frozen samples.[https://github.com/greenelab/pancancer/]</p> <p>6) cosmic_cancer_classification.tsv: Compendium of OG and TSG used for the analysis. Added additional genes from the cosmic database to volgelstein_cancer_classification.tsv [https://github.com/greenelab/pancancer/]</p> <p>7) CCLE_DepMap_18Q1_maf_20180207.txt.gz Publicly available Mutational data for CCLE cell lines from Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2FCCLE_DepMap_18Q1_maf_20180207.txt]</p> <p>8) ccle_rnaseq_genes_rpkm_20180929_mod.tsv.gz: Publicly available Expression data for 1019 cell lines (RPKM) from Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://depmap.org/portal/download/api/download/external?file_name=ccle%2Fccle_2019%2FCCLE_RNAseq_genes_rpkm_20180929.gct.gz]</p> <p>9) CCLE_MUT_CNA_AMP_DEL_binary_Revealer.tsv: Publicly available merged Mutational and copy number alterations that include gene amplifications and deletions for the CCLE cell lines. This data is represented in the binary format and provided by the Broad Institute Cancer Cell Line Encyclopedia (CCLE) / DepMap Portal. [https://data.broadinstitute.org/ccle_legacy_data/binary_calls_for_copy_number_and_mutation_data/CCLE_MUT_CNA_AMP_DEL_binary_Revealer.gct]</p> <p>10) GDSC_cell_lines_EXP_CCLE_names.tsv.gz Publicly available RMA normalized expression data for Genomics of Drug Sensitivity in Cancer(GDSC) cell-lines. File gdsc_cell_line_RMA_proc_basalExp.csv was downloaded. This data was subsetted to 389 cell lines that are common among CCLE and GDSC. All the GDSC cell line names were replaced with CCLE cell line names for further processing. [https://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources//Data/preprocessed/Cell_line_RMA_proc_basalExp.txt.zip]</p> <p>11) GDSC_CCLE_common_mut_cnv_binary.tsv.gz: A subset of merged Mutational and copy number alterations that include gene amplifications and deletions for common cell lines between GDSC and CCLE. This file is generated using CCLE_MUT_CNA_AMP_DEL_binary_Revealer.tsv and a list of common cell lines. </p> <p>12) gdsc1_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC1 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC1_fitted_dose_response_15Oct19.xlsx]</p> <p>13) gdsc2_ccle_pharm_fitted_dose_data.txt.gz: Pharmacological data for GDSC2 cell lines. [ftp://ftp.sanger.ac.uk/pub/project/cancerrxgene/releases/current_release/GDSC2_fitted_dose_response_15Oct19.xlsx]</p> <p>14) compounds_of_interest.txt: list of pharmacological compounds tested for our analysis, taken from ftp://ftp.sanger.ac.uk/pub4/cancerrxgene/releases/release-8.1/screened_compounds_rel_8.1.csv. </p> <p>15) tcga_dictonary.tsv: list of cancer types used in the analysis. </p> <p>16) seg_based_scores.tsv: Measurement of total copy number burden, Percent of genome altered by copy number alterations. This file was used as part of the Pancancer analysis by Gregory Way et al as described in https://github.com/greenelab/pancancer/ data processing and initialization steps. [https://github.com/greenelab/pancancer/]</p> <p>17) GSE69822_pi3k_sign.txt: File with values assigned for tumor [1] or normal [-1] in given external samples (GSE69822)</p> <p>18) vlog_trans.csv: Variant stabilized log-transformed expression values in given external samples (GSE69822)</p> <p>19) path_rtk_ras_pi3k_genes.txt: File with the list of ERK/RAS/PI3K pathway genes used in the analysis. </p> <p>20) path_myc_genes.txt: File with the list of Myc pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>21) path_ras_genes.txt: File with the list of RAS pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>22) path_cell_cycle_genes.txt: File with the list of cell cycle pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>23) path_wnt_genes.txt: File with the list of WNT pathway genes used in the analysis. (Sanchez-Vega, Francisco et al.)</p> <p>24) GSE94937_rpkm_kras.csv: Expression values in given external samples (GSE94937)</p> <p>25) GSE94937_kras_sign.txt: File with values assigned for KRAS Mutant [1] or WT [-1] in given external samples (GSE94937)</p>
Data from: Pathways of cryptic invasion in a fish parasite traced using coalescent analysis and epidemiological survey
Introduced species have the potential to outperform natives via the introduction of new parasites to which the native ecosystem is vulnerable. Cryptic diversity within an invasive species can obscure invasion patterns and confound proper management measures. The aim of this study is to use coalescent theory based methodology to trace recent routes of invasion in populations of Ligula intestinalis, a globally distributed fish parasite possessing both native and recently introduced populations in North Africa. Molecular analyses of mitochondrial DNA discerned a pronounced genetic divergence between introduced and native populations. Distribution of mitochondrial haplotypes demonstrated common origin of European populations with North African parasites sampled from introduced fish species in Tunisia. To test the suggested pathway of introduction, microsatellite data were examined in a model-based coalescent analysis using the software MIGRATE, where Europe to Tunisia direction of migration was favoured over alternative hypotheses of gene flow. Specificity of Tunisian populations to different host species was assessed in an epidemiologic survey confirming prevailing host-based division between introduced and native parasites in North Africa. This approach combining advanced analysis of molecular markers with host-specificity data allows revealing the evolution of host-parasite interactions following biological invasion and provides basis for devising future management measurements.
Uncoupling of Behavioral and Metabolic Twenty-Four-Hour Rhythms in Reindeer (Current Biology, Meier et al. 2024): Metabolomics analysis tables: Annotation list, pathway analysis outputs, target list for targeted peak exstraction and MS/MS spectra of annotated features
<p><span>Metabolomics analysis tables: Annotation list, pathway analysis outputs, target list for targeted peak exstraction and MS/MS spectra of annotated features</span></p>
Transcriptomic analysis reveals potential candidate pathways and genes involved in toxin biosynthesis in true toads
<p>Synthesized chemical defenses have broadly evolved across countless taxa and are important in 30 shaping evolutionary and ecological interactions within ecosystems. However, the underlying 31 genomic mechanisms by which these organisms synthesize and utilize their toxins are relatively 32 unknown. Herein, we use comparative transcriptomics to uncover potential toxin synthesizing 33 genes and pathways, as well as interspecific patterns of toxin synthesizing genes across ten 34 species of North American true toads (Bufonidae). Upon assembly and annotation of the ten 35 transcriptomes, we explored patterns of relative gene expression and possible protein-protein 36 interactions across the species to determine what genes and/or pathways may be responsible for 37 toxin synthesis. We also tested our transcriptome dataset for signatures of positive selection to 38 reveal how selection may be acting upon potential toxin producing genes. We assembled high 39 quality transcriptomes of the bufonid parotoid gland, a tissue not often investigated in other 40 bufonid related RNAseq studies. We found several genes involved in metabolic and biosynthetic 41 pathways (e.g. steroid biosynthesis, terpenoid backbone biosynthesis, isoquinoline biosynthesis, 42 glucosinolate biosynthesis) that were functionally enriched and/or relatively expressed across the 43 ten focal species that may be involved in the synthesis of alkaloid and steroid toxins, as well as 44 other small metabolic compounds that cause distastefulness in bufonids. We hope that our study 45 lays a foundation for future studies to explore the genomic underpinnings and specific pathways 46 of toxin synthesis in toads, as well as at the macroevolutionary scale across numerous taxa that 47 produce their own defensive toxins.</p>
Supplementary material 1 from: Wilson CE, Castro KL, Thurston GB, Sissons A (2016) Pathway risk analysis of weed seeds in imported grain: A Canadian perspective. In: Daehler CC, van Kleunen M, Pyšek P, Richardson DM (Eds) Proceedings of 13th International EMAPi conference, Waikoloa, Hawaii. NeoBiota 30: 49–74. https://doi.org/10.3897/neobiota.30.7502
Weed seed contaminant species reported in imported grain in a Canadian sampling program 2007–2015 : Explanation note: Complete list of weed seed contaminant species reported in 947 samples of 10 imported grain crops in a Canadian sampling program 2007–2015, cross-listed to number of times reported and crops reported in.
Supplementary material 2 from: Wilson CE, Castro KL, Thurston GB, Sissons A (2016) Pathway risk analysis of weed seeds in imported grain: A Canadian perspective. In: Daehler CC, van Kleunen M, Pyšek P, Richardson DM (Eds) Proceedings of 13th International EMAPi conference, Waikoloa, Hawaii. NeoBiota 30: 49–74. https://doi.org/10.3897/neobiota.30.7502
Frequency distributions showing percentage samples with number of contaminant species reported per sample for 10 imported grain crops examined in a Canadian sampling program 2007–2015 : Explanation note: Ten frequency distribution graphs (one per crop) shown in a multi-panel.
Aviation Fuel Production Pathways from Lignocellulosic Biomass via Alcohol Intermediates – A Technical Analysis - Supplementary Material
<p>Data for the associated publication </p>
Analysis of mitochondrial respiratory pathway and coupling control by substrate-uncoupler-inhibitor titration reference protocols
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Supplementary tables for the paper: "Comprehensive computational analysis via Adverse Outcome Pathways and Aggregate Exposure Pathways in exploring synergistic effects from radon and tobacco smoke on lung cancer."
<p><strong>Authors</strong>:<br>Thomas Jaylet, Vinita Chauhan, Laura Mezquita, <em>Nadia Boroumand</em><em>, </em>Olivier Laurent, <em>Karine Elihn</em><em>, Lovisa Lundholm</em><em>, </em>Olivier Armant, Karine Audouze</p>
Data set of the article "Comparative analysis of the unbinding pathways of antiviral drug Indinavir from HIV and HTLV1 proteases by supervised molecular dynamics simulation"
<p>Data set of the article "Comparative analysis of the unbinding pathways of antiviral drug Indinavir from HIV and HTLV1 proteases by supervised molecular dynamics simulation"</p>
Fig. 5 in L-DOPA synthesis in Mucuna pruriens (L.) DC. is regulated by polyphenol oxidase and not CYP 450/tyrosine hydroxylase: An analysis of metabolic pathway using biochemical and molecular markers
Fig. 5. The amplicons generated using degenerate primer approach. (a) Lane M-DNA ladder, Lane 1–250 bp amplicon generated using MTH –F and MTH-R primer pairs of TH gene (b) Lane M-DNA ladder, Lane 1 and 2–800 bp amplicon using primers deduced from the peptide sequence derived through LCMS/MS.
Fig. 4 in L-DOPA synthesis in Mucuna pruriens (L.) DC. is regulated by polyphenol oxidase and not CYP 450/tyrosine hydroxylase: An analysis of metabolic pathway using biochemical and molecular markers
Fig. 4. Effect of enzyme inhibitors on L-DOPA production in callus cultures of M. pruriens was estimated using HPTLC. The culture without inhibitor was treated as negative control and cultures with different concentration of the inhibitor were the test samples. (Control-untreated, C = Cimetidine at 1.98 μM and 19.8 μM; Q = Quinidine at 1.46 μM and 14.6 μM; A = L-ascorbic acid at 567 μM and 851 μM; K = Kojic acid at 703 μM and 1055 μM).
Fig. 3 in L-DOPA synthesis in Mucuna pruriens (L.) DC. is regulated by polyphenol oxidase and not CYP 450/tyrosine hydroxylase: An analysis of metabolic pathway using biochemical and molecular markers
Fig. 3. Effect of substrate concentration on partially purified enzymes. The assay was performed for PPO activity with 50 mM catechol as substrate at pH 6.0 while keeping the temperature for reaction at 30 ◦ C. For TH activity, 30 mM L-tyrosine was the substrate and assay done at pH 7.0 and 25 ◦ C.
ScienceDex guides
Understand access before you commit
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.