Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
16
datasets available to search
ShareScore release 0.9.0
Dataset results
16 results for “molecular visualization”
Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses
<p>Raw data and code to reproduce figures in the manuscript "Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses"</p> <p># README</p> <p>## Introduction</p> <p>This README provides essential information about the codebase for the manuscript titled "Molecularly targetable cell types in mouse visual cortex have distinguishable prediction error responses." The code in this repository is self-contained and is expected to run smoothly given the appropriate versions of the required libraries/packages.</p> <p>## Directory structure and execution details</p> <p>### R code</p> <p>- Main Figures 2A-2D, 3A-3C, and 4A-4E, as well as supplemental figures S2A-S2H, S3A-S3E, S4L, and S5A-S5I, were generated using R. Execute the `R_figs_master.r` script located in the `r_code` directory.<br> - All figures will be saved within the `r_code/code_generated_figures` directory.<br> - Note: Exact UMAP representations might vary across different hardware and operating systems, likely due to an issue with the UWOT package ([Reference Issue](https://github.com/satijalab/seurat/issues/5514)). If figures appear outside their designated plot ranges, set "FixAxes" to 'FALSE' in the `single_cell_variables.r` script.</p> <p>### MATLAB code</p> <p>- Main figures 1B, 1D-1F, and 6A-6H, as well as supplemental figures S1A-S1J and S6A-S6I, were generated using MATLAB (version 9.11.0.1809720 (R2021b) Update 1). Execute the `get_the_figs_matlab.m` script located in the `matlab_code` directory.<br> - All figures will be saved within the `matlab_code/code_generated_figures` directory.<br> - Required: [fca_readfcs, version 2020.06.22](https://ch.mathworks.com/matlabcentral/fileexchange/9608-fca_readfcs).</p> <p>### Python code</p> <p>- Figures 5B-5F panels were generated using Python (version 3.6.8). Run the `fig_5_analysis_code.py` script located in the `python_code` directory.<br> - All figures will be saved within the `python_code/code_generated_figures` directory.<br> - The preprocessed images located in `python_code/data_repository/Adamts2_processed`, `python_code/data_repository/Agmat_processed`, and `python_code/data_repository/Baz1a_processed` were generated using the ImageJ macro `python_code/cropped_to_processed_macro.ijm` from the raw images in `python_code/data_repository/Adamts2_cropped`, `python_code/data_repository/Agmat_cropped`, and `python_code/data_repository/Baz1a_cropped`.</p> <p>## Supplementary code (for reference only as raw data is not included)</p> <p>### Mapping code and genome construction code</p> <p>- Initial processing of Single-cell RNA-sequencing was performed with Cell Ranger, coordinated by the Python script:<br> `python_code/mapping_and_genome_construction/single_cell_mapping_pipeline.py`. Some components of this script are deprecated and were primarily used to pass .fastq files to Cell Ranger and organize the outputs.<br> - A custom genome was constructed to account for the expression of CaMPARI2 in the single-cell RNA-sequencing dataset:<br> `python_code/mapping_and_genome_construction/campari2_genome_construction.py`.<br> - Processing of Bulk RNA-sequencing, either single or paired-end, was executed through Python:<br> `python_code/mapping_and_genome_construction/bulk_single_end_mapping.py` and `python_code/mapping_and_genome_construction/bulk_paired_end_mapping.py`.<br> - A custom genome was constructed to account for the expression of various artificial promoter viruses:<br> `python_code/mapping_and_genome_construction/bulk_seq_genome_construction.py`.</p>
Data from: Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs
<p>Dataset for the article Diversity and molecular evolution of non-visual opsin genes across environmental, developmental, and morphological adaptations in frogs. Includes non-visual opsin coding sequences from frogs, sequence alingments, phylogenetics trees, and raw PAML results files.</p>
Complementary molecular and visual sampling of fish on oil and gas platforms provides superior biodiversity characterisation
<p>Raw data output from Fish and Elasmobranch surveys on oil platforms in the Gulf of Thailand</p>
Molecular Evolution of Tuatara Visual System Datasets: Supporting Data for the Tuatara Genome
<p>Datasets associated with the Molecular Evolution of Tuatara Visual System supplement to the paper: The Tuatara Genome: Insights into Vertebrate Evolution from the Sole Survivor of an Ancient Reptilian Order.</p>
Data from: Pigment molecular composition reveals significant information for visual communication
<p>1. Melanins are the most common pigments in vertebrates and, as such, fufill multiple adaptive functions, including honest signaling. This is the case of male pied flycatchers Ficedula hypoleuca, whose dorsal plumage, composed of black and grey feathers pigmented by eumelanin, is sexually selected by females regarding the proportion of black.</p> <p>2. However, the basis of such mating preferences and other associations with life-history traits are unknown. </p> <p>3. Here I take advantage of recent advances in Raman spectroscopy analysis to investigate the monomeric composition of eumelanin, constituted by 5,6-dihydroxyindole (DHI) and 5,6-dihydroxyindole-2-carboxylic acid (DHICA) subunits, in male pied flycatchers. </p> <p>4. I found that plumage blackness (percentage of dorsal black feathers) increases with the DHICA:DHI ratio of the constituent black freathers, but not with that of grey feathers. The repeatability of DHICA:DHI measurements in black feathers is two times that in grey feathers. </p> <p>5. Eumelanin chemistry may thus constitute the basis of signal honesty in pied flycatchers, as females preferentially mate with males with higher relative DHICA feather contents and this may be related to the lower pro-oxidant effect of DHICA. Given the the ubiquitous nature of melanin-based pigmentation phenotypes, the monomeric composition of eumelanin should therefore be considered, instead of eumelanin as a whole, for a better understanding of how and why phenotypes are linked to life-history traits in animals.</p>
Data from: Pigment molecular composition reveals significant information for visual communication
Open the record for dataset details and reuse information.
A single-cell atlas of bobtail squid visual and nervous system highlights molecular principles of convergent evolution
GEO Series GSE203527. Euprymna berryi. 74 samples. Type: Expression profiling by high throughput sequencing.
Microsatellite expansion RNA visualization, elimination, and reversal of molecular pathology by RNA-targeting Cas9
GEO Series GSE100943. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Cell types and molecular architecture of the Octopus bimaculoides visual system
GEO Series GSE212528. Octopus bimaculoides. 4 samples. Type: Expression profiling by high throughput sequencing.
Mapping Visual Functions onto Molecular Cell Types in the Mouse Superior Colliculus
GEO Series GSE223155. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
Visual Study of Molecular Genotype in Glioma Evolution
ClinicalTrials.gov study NCT03750890. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Molecular Imaging Visualization of Tumor Heterogeneity in Non-small Cell Lung Cancer
ClinicalTrials.gov study NCT04553601. IPD Sharing: NO. Countries: 1. Publications: 0.
Application of Three- Dimensional Visualization Combined With ICG Molecular Fluorescence Imaging in Hepatolithiasis
ClinicalTrials.gov study NCT06447181. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Improvement of the Operative Outcome in Patients With Primary VEGF + Unifocal Breast Cancer or DCIS Through the Intraoperative Visualization of the Tumor Using Molecular Imaging and Bevacizumab-IRDye-
ClinicalTrials.gov study NCT05359874. IPD Sharing: UNDECIDED. Countries: 0. Publications: 0.
Visual automated fluorescence electrophoresis provides simultaneous quality, quantity, and molecular weight spectra for genomic DNA from archived neonatal blood spots
GEO Series GSE44249. Homo sapiens. 8 samples. Type: Genome variation profiling by array.
PharmaVQA: A Retrieval-Augmented Visual Question Answering Framework for Molecular Representation via Pharmacophores Guided Prompts
<p>The dataset includes the preprocessed Li's dataset, MoleculeACE dataset, and 3 ligands dataset.</p>
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.