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11,177 results for “identify”
Fig. 3 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage
Fig. 3. Differential expressed gene analysis (DEG) of transcriptome. DEG in Volcano plot (log transform of early exponential growth and early stationary growth phases versus inverse log Padj – corrected P-value). Up-regulated DEGs are in red color dots, down-regulated DEGs are in blue dots, while grey dots represent no significant DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage
Fig. 2. Transcriptome expression analysis during different growth stages. (a) Venn diagram for specific treatment genes. Venn diagram constructed based on subset between gene pools in the early exponential and early stationary growth phases of M. gracile SEMC4 cultures. The total number of early exponential growth-specific (EEG-specific) genes (blue subset); early stationary growth-specific (ESG-specific) genes (pink sub set) and regulatory genes (purple sub set) are as indicated. (b) Soft clustering based on time series analysis on expression changes between early exponential growth and early stationary growth phases of M. gracile SE-MC4 cultures. R1, R2 and R3 are the biological replicates of each early exponential (day 1) and early stationary (day 12) growth phase of M. gracile SE-MC4 cultures. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in Phytochemical profiling of several Hypericum species identified using genetic markers
Fig. 4. PCA (A) and HCA (B) analyses of 13 metabolites quantified in the extracts of shoots of ex vitro grown Hypericum plants. The PCA biplot (A) shows grouping of the species (points), and the contribution (loadings) of the variables (metabolites, indicated by the arrows) to the grouping. Each species is represented by three biological replicates (three points per species). The points are colored according to their quality of representation on the factor map, expressed by squared cosine (cos2). The direction and length of the loading vectors show how each metabolite contributes to clustering. An ellipse is drawn around each cluster. The species are clustered according to the branches as depicted at HCA dendrogram (B). Each square in the heatmap dendrogram represents the relative content of a metabolite. The red and blue color represent an increase and a decrease of relative metabolite content, respectively. Different color of metabolites (PCA) or lines under the heatmap (HCA) indicate the metabolite contents in leaves (green) and stems (brown). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Phytochemical profiling of several Hypericum species identified using genetic markers
Fig. 3. PCA (A) and HCA (B) analyses of 13 metabolites quantified in the extracts of shoots of in vitro-grown Hypericum plants. The PCA biplot (A) shows grouping of the species (points), and the contribution (loadings) of the variables (metabolites, indicated by the arrows) to the grouping. Each species is represented by three biological replicates (three points per species). The points are colored according to their quality of representation on the factor map, expressed by squared cosine (cos2). The direction and length of the loading vectors show how each metabolite contributes to clustering. An ellipse is drawn around each cluster. The species are clustered according to the branches as depicted at HCA dendrogram (B). Each square in the heatmap dendrogram represents the relative content of a metabolite. The red and blue color represent an increase and a decrease of relative metabolite content, respectively. Different color of metabolites (PCA) or lines under the heatmap (HCA) indicate the metabolite contents in leaves (green) and stems (brown). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Phytochemical profiling of several Hypericum species identified using genetic markers
Fig. 2. Metaphase chromosomes in root tip squashes of several representatives of the genus Hypericum arranged in ascending order from the lowest to the highest value of the DNA content per chromosome: H. xylosteifolium, 2n =40 (A), H. androsaemum, 2n =40 (B), H. hircinum, 2n =40 (C), H. athoum, 2n =16 (D), H. empetrifolium, 2n =18 (E), H. atomarium, 2n =16 (F), H. monogynum, 2n =42 (G), H. stellatum, 2n =18, 20 (H), H. patulum, 2n =36 (I). Photo: S. Hovancov´a.
Identifying 'climate keystone species' as a tool for conserving ecosystem functioning under climate change
<p><strong>Aim</strong>: Climate change affects ecological communities via impacts on species. The community's response to climate change can be represented as the temporal trend in a climate-related functional property that is quantified using a relevant functional trait. Noteworthy, some species influence this response in the community more strongly than others.</p> <p><strong>Innovation</strong>: Leveraging on the concept of keystone species, we propose that species with a strong effect on the community's functional response to climate change beyond their relative abundance can be considered as 'climate keystone species'. We develop a stepwise tool to determine species' effects on a community's climate response and identify climate keystone species. We quantify the species-specific effect by measuring the difference in the community's climate response with and without the species. Next, we identify climate keystone species as those with a strong residual effect after weighting with their relative abundances in the community.</p> <p><strong>Main</strong> <strong>Conclusions</strong>: To illustrate the use of the stepwise tool with empirical data, we identify climate keystone species that have a strong effect on the change in the average temperature niche in North American bird communities over time and find the identification tool ecologically relevant. Identification of climate keystone species can serve as an additional conservation method to efficiently protect ecosystem functions.</p>
High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival
<p>Annotated single cell count data for "High-dimensional deconstruction of pancreatic cancer identifies tumor microenvironmental and developmental stemness features that predict survival"</p>
Identifying perturbations that tipped the stratosphere into a sudden warming during January 2013
<p>Climate model data utilised to create the paper figures.</p>
Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations (Data)
<p>README file for LBL-ERA5, LBL-GCM, and band datasets used in:<br> Raghuraman et al., 2023, Geophysical Research Letters,<br> "Greenhouse gas forcing and climate feedback signatures identified in hyperspectral infrared satellite observations "</p> <p>Point of Contact: Shiv Priyam Raghuraman, shivr@alumni.princeton.edu</p> <p> </p> <p>LBL-ERA5</p> <p>6 files (3 experiments with olr and olr_clr output separately):</p> <p>2003-2021.GFDL.all-2010-o3_*.nc - varying WMGHG,Ts,T,q,clouds, fixed o3</p> <p>2003-2021.GFDL.fo3_*.nc - varying WMGHG and fixed Ts,T,q,clouds,surface albedo,o3</p> <p>2003-2021.GFDL.ff_*.nc - fixed Ts,T,q,clouds,surface albedo, varying o3</p> <p> </p> <p>LBL-GCM (clear-sky only)</p> <p>4 AM4 files:</p> <p>AM4piclim-control.nc (for ERF)</p> <p>AM4piclim-4xCO2_1xCO2IRF.nc (for ERF)</p> <p>AM4piclim-control_STRAT.nc (for SARF)</p> <p>AM4piclim-4xCO2_1xCO2IRF_STRAT.nc (for SARF)</p> <p>4 CM3/AM3 files:</p> <p>CTLAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>EXPAM3CM3_P1_APR_allctm_E1_RFM_1CM_A2_WN3_1xCO2N.nc (for \lambda)</p> <p>CTLAM3CM3_P1_2003C.nc (for IRF)</p> <p>CTLAM3CM3_P1_2021C.nc (for IRF)</p> <p> </p> <p>Band-AM4/MERRA-Total: GFDL AM4 with prescribed SSTs and sea-ice (AMIP) and nudged with MERRA winds</p> <p>2 files:</p> <p>atmos.200001-202112.olr.nc - all-sky OLR</p> <p>atmos.200001-202112.olr_clr.nc - clear-sky OLR</p> <p> </p> <p>Observational and reanalysis files used in paper (AIRS, CERES EBAF and SSF, GISTEMP, ERA5 input data) can be downloaded from their respective websites (see paper's "Open Research" section).</p> <p> </p>
Dataset - Methods to Authenticate Luxury Products: Identifying Key Features and Most Recognized Deficits
<p>This is a complementary dataset for the papers:</p> <p>Zimmermann, R., Udokwu, C. J., Kompp, R., Brandtner, P., & Norta, A. (2022). Authentication of Luxury Products – Identifying Key Requirements from a Seller and Consumer Perspective. <em>Communications in Computer and Information Science</em>, 195-209. https://doi.org/10.1007/978-981-19-8069-5_13</p> <p>Zimmermann, R., Udokwu, C. J., Kompp, R., Staab, M., Brandtner, P., & Norta, A. (In Press). Dataset - Methods to Authenticate Luxury Products: Identifying Key Features and Most Recognized Deficits. <em>SN Computer Science. DOI: 10.1007/s42979-023-02201-5.</em></p>
Color profiles of 108 UDGs identified in HFF fields
<p>Multi-band surface brightness profiles of 108 UDGs identified in HFF fields. Details about each diagram are listed below.<br> Panels\,(1) to (3) show the F814W band cutout-images of the UDG, the best-fitting GALFIT model and residual image. The bar at top-right of panel\,(2) represents 1.5\,kpc assuming the cluster redshift.<br> Panels\,(4) to (6) show PSF-matched images in F606W, F814W and F160W bands.<br> In panels\,(7) to (9), we mask neighboring sources classified by `Noisechisel' and overplot our elliptical annuli used in surface brightness analysis.<br> Panel\,(10) presents three-band surface brightness profiles of each UDG,<br> x-axis of colorful points correspond to the out-radius of elliptical annuli.<br> In panel\,(11), we convert observed color profiles into rest-frame U\,-\,V and V\,-\,I profiles.<br> F814W and F160W surface brightness profiles in panel\,(10) and rest-frame V\,-\,I profiles in panel\,(11) are shifted a bit to the right.<br> Finally, the colors of the UDG from inside to outside are shown in the UVI diagram in panel\,(12).<br> Please note that for UDGs which do not have F160W observations will not have panels (6),(9),(12).</p>
Comprehensive genomic analysis identifies a diverse landscape of sideroblastic and non-sideroblastic iron related anemias with novel and pathogenic variants in an iron deficient endemic setting
<p>The history for the 5 CMA cases are as follows:-</p> <p> </p> <p>1. <strong>HMA-2 </strong>:- 0.6 month male child presented with poor feeding and noted to have mild-moderate pallor. CBC showed Hemoglobin 9.0gm/dl, MCV- 58fl, MCH 17.3, MCHC 29, Iron 113 ug/dl, Ferritin 297 ug/l, TSAT-45%, TIBC-297 ug/dl, Hepcidin- 20.3ng/ml. No transfusions received and antenatal and neonatal history uneventful. HPLC (both parents), alpha sequencing normal. Targeted NGS shows a heterozygous VUS in GLRX5 gene along with a VUS in BMP6 gene. WES- Does not add anything further significant.</p> <p> </p> <p>2. <strong>HMA-3 </strong>:- 0.8 month male child with transfusion dependent microcytic hypochromic anemia and neurological developmental delay. Expired at 1 year of age due to secondary infection (acinetobacter and toxoplasmosis). Hb- 6.5, MCV-61.5, MCH-18.3, Iron 45 ug/dl, Ferritin 650. Targeted panel and WES - negative.</p> <p> </p> <p>3. <strong>HMA-4:</strong>- 5 year male child with severe microcytic hypochromic anemia and received just one transfusion outside. Has microcephaly and SNHL. Hb 5, MCV- 56, MCH- 18, MCHC- 23, Iron- 75, Ferritin - 330, TIBC- 290, TSAT- 41%. Targeted NGS and WES show a Homozygous VUS in BMP6 gene (? association?) </p> <p> </p> <p>4. <strong>HMA-6:-</strong> 2 year old male child with moderate microcytic hypochromic anemia and focal seizures. Hb -8, MCV- 58, MCH- 16, MCHC-27, Iron- 94, Ferritin -380, Transferrin levels- 10 (very low). Targeted NGS and WES show a single heterozygous VUS mutation in TF gene and another intrinsic rare variant but reported in pop. Database (could it make it compound her for atransferrinemia?) </p> <p> </p> <p>5. <strong>HMA-7:-</strong> 7 year male child with short stature, consanguinity in family, moderate macrocytic anemia with HB-7, MCV-113, Iron-55, Ferritin -209, TSAT-54%. Also Bone marrow shows coarse vacuolations in erythroid cells (12%) and 19% RS. Suspicion PMS- But MLPA for mitochondrial genome normal, no deletions. Targeted panel NGS and WES reveal a heterozygous VUS in LARS2 gene (? nature).</p> <p> </p>
Population genomics of an Octopus species identify oceanographic barriers and inbreeding patterns: Demultiplexed reads of 71 Octopus insularis individuals
<p>Coastal marine ecosystems are highly productive and important for global fisheries. To mitigate over-exploitation and to establish efficient conservation management plans for species of economic interest, it is necessary to identify the oceanographic barriers that condition divergence and gene flow between populations with those species, and that determine their relative amounts of genetic variability. Here, we present the first population genomic study of an <em>Octopus</em> species, <em>Octopus</em> <em>insularis</em>, which was described in 2008 and is distributed in coastal and oceanic island habitats in the tropical Atlantic Ocean, Gulf of Mexico and the Caribbean Sea. Using genomic data, we identify the South Equatorial current as the main barrier to gene flow between southern and northern parts of the range, followed by discontinuities in the habitat associated with depth. We find that genetic diversity of insular populations significantly decreases after colonization from the continental shelf, also reflecting low habitat availability. Using demographic modelling, we find signatures of a stronger population expansion for coastal relative to insular populations, consistent with estimated increases in habitat availability since the Last Glacial Maximum. The direction of gene flow is coincident with unidirectional currents and bidirectional eddies between otherwise isolated populations. Together, our results show that oceanic currents and habitat breaks are determinant in the diversification of coastal marine species where adults have a sedentary behavior but paralarvae are dispersed passively, shaping standing genetic variability within populations. Lower genetic diversity within insular populations implies that these are particularly vulnerable to current human exploitation and selective pressures, calling for the revision of their protection status.</p>
MarTREC Data Set for Report: Developing and Applying an Analysis Methodology to Identify Flow Generation Influences between Vessel and Truck Shipments
<p>Truck activity is logically connected to vessel activity at a port. In turn, vessel activity is also influenced by truck shipments. Although one might expect a direct and straightforward relation between these two types of shipments, that is rarely the case. For instance, many maritime containers carry consolidated cargos that have multiple and different final destinations. Also, different truck capacities, customs clearance and regulations play a critical role in determining the actual relation between these two types of shipments. This project aims at shedding light on the nuances of maritime and roadway flow relations by quantitatively analyzing the linkages between these two types of shipments.</p> <p>The study performed a statistical analysis to determine the probability distributions of vessel and truck activity, and then explore the correlation of each activity with the other. The analysis yielded coefficients that function as explanatory values for specific truck flows.</p> <p>The ultimate purpose of this study is to provide a clearer and quantitative understanding of the relationship between maritime and truck shipments, and by doing so, to provide tools to develop a system for managing trucks that maximizes efficiency for industry, while minimizing industry’s negative impacts on a region.</p> <p>For this purpose, the study selected the Port Freeport as a case study.</p>
Don't Treat Ghosts Anti-MRSA Antibiotics in Osteomyelitis Without Identified MRSA
ClinicalTrials.gov study NCT06096012. IPD Sharing: YES. Countries: 1. Publications: 2.
Identify the Usefulness of Peer-facilitated Versus Self-navigated Quit Tobacco Program for Youths.
ClinicalTrials.gov study NCT06053762. IPD Sharing: NO. Countries: 1. Publications: 22.
Prospective Project to Identify Biomarkers of Morbidity and Mortality in Cardiovascular Interventional Patients
ClinicalTrials.gov study NCT03444259. IPD Sharing: UNDECIDED. Countries: 1. Publications: 3.
Identify Prognostic Biomarkers of Lung Cancer
ClinicalTrials.gov study NCT05010330. IPD Sharing: NO. Countries: 1. Publications: 1.
Genomic Analysis to Identify a Predictive Biomarker for Immunotherapy
ClinicalTrials.gov study NCT03578185. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Functional Imaging to Identify Radiosensitive Esophageal Cancer - a Biomarker Validation Study
ClinicalTrials.gov study NCT06189898. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
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.