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Dataset results
17 results for “signal alignment”
Data from: Control of signaling alignment during the dynamic courtship display of a jumping spider
During communication, alignment between signals and sensors can be critical. Signals are often best perceived from specific angles, and sensory systems can also exhibit strong directional biases. However, we know little about how animals establish and maintain such signaling alignment during communication. To investigate this, we characterized the spatial dynamics of visual courtship signaling in the jumping spider Habronattus pyrrithrix. The male performs forward-facing displays involving complex color and movement patterns, with distinct long- and short-range phases. The female views displays with 2 distinct eye types and can only perceive colors and fine patterns of male displays when they are presented in her frontal field of view. Whether and how courtship interactions produce such alignment between male display and female field of view is unknown. We recorded relative positions and orientations of both actors throughout courtship and established the role of each sex in maintaining signaling alignment. Males always oriented their displays toward the female. However, when females were free to move, male displays were consistently aligned with female principal eyes only during short-range courtship. When female position was fixed, signaling alignment consistently occurred during both phases, suggesting that female movement reduces communication efficacy. When female models were experimentally rotated to face away during courtship, males rarely repositioned themselves to re-align their display. However, males were more likely to present certain display elements after females turned to face them. Thus, although signaling alignment is a function of both sexes, males appear to rely on female behavior for effective communication.
Dataset and code related to the publication "Aligning heat pump operation with market signals: A win-win scenario for the electricity market and its actors?"
<h3>General remarks</h3> <p>This dataset and code was developed and used for the publication</p> <blockquote> <p><em>E. Sperber, C. Schimeczek, U. Frey, K. K. Cao, V. Bertsch: Aligning heat pump operation with market signals: A win-win scenario for the electricity market and its actors? In: Energy Reports, Volume 13, June 2025, pp. 491-513, https://doi.org/10.1016/j.egyr.2024.12.028<br></em></p> </blockquote> <h3>Data description</h3> <p>The dataset "<em>heat_pump_results.zip</em>" includes all relevant results underlying the above publication. </p> <p>The data is organized according to the scenarios considered in the analysis. Therefore, each folder is labelled according to the scenario structure, starting with the building efficiency scenario ("BAU" / "EFF"), followed by the PV scenario ("no-PV" / "with-PV"), the HP operation scenario ("ModFlex_V", "ModFlex_F", "HighFlex_V"), the simulation year (2030 / 2040) and the weather year (2017 / 2019 / 2023).</p> <p>Within each result directory per scenario, the data is further structured according to the results at the market level ("AMIRIS") and at the user level ("GAMS" and "INFLEX"). The "INFLEX" directory contains results for the inflexible reference operation, while the "GAMS" directory contains results for the cost-minimized heat pump operation at the level of building types. The data at the user level is further structured by location. Data is given in hourly resolution.</p> <p>The scenario evaluation indicators presented in the publication, as well as other indicators, are summarized in the "MPI" directory.</p> <p>Abbreviations used:</p> <ul> <li>HP: heat pump</li> <li>SH: space heating</li> <li>DHW: domestic hot water</li> <li>AW: air/water</li> <li>BW: brine/water</li> <li>PV: photovoltaic</li> <li>Ti: indoor air temperature</li> <li>Ttes: temperature of domestic hot water storage tank</li> </ul> <h3>Code description</h3> <p>The code to generate the results is given in "<em>heat_pump_workflow.zip</em>". Please follow the instructions in the README.md that you can find in this archive.</p> <h3>Conctact</h3> <p>Please contact Evelyn Sperber at evelyn.sperber@dlr.de if you have any questions.</p>
Confocal images from: Cell density, alignment, and orientation correlate with C-signal-dependent gene expression during Myxococcus xanthus development
<p>Starving <em>Myxococcus xanthus</em> bacteria use short-range C-signaling to coordinate their movements and construct multicellular mounds, which mature into fruiting bodies as rods differentiate into spherical spores. Differentiation requires efficient C-signaling to drive the expression of developmental genes, but how the arrangement of cells within nascent fruiting bodies (NFBs) affects C-signaling is not fully understood. Here, we used confocal microscopy and cell segmentation to visualize and quantify the arrangement, morphology, and gene expression of cells near the bottom of NFBs at much higher resolution than previously achieved. We discovered that "transitioning cells" (TCs), intermediate in morphology between rods and spores, comprised 10 to 15% of the total population. Spores appeared midway between the center and the edge of NFBs early in their development and near the center as maturation progressed. The developmental pattern as well as C-signal-dependent gene expression in TCs and spores were correlated with cell density, the alignment of neighboring rods, and the tangential orientation of rods early in the development of NFBs. These dynamic radial patterns support a model in which the arrangement of cells within the NFBs affects C-signaling efficiency to regulate precisely the expression of developmental genes and cellular differentiation in space and time. Developmental patterns in other bacterial biofilms may likewise rely on short-range signaling to communicate multiple aspects of cellular arrangement, analogous to juxtacrine and paracrine signaling during animal development.</p>
Artificial signal data for signal alignment testing.
<p>This is a set of signals-pairs, univariate and multivariate, that can be used to test alignment algorithms.</p>
Confocal images from: Cell density, alignment, and orientation correlate with C-signal-dependent gene expression during Myxococcus xanthus development
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Data from: Control of signaling alignment during the dynamic courtship display of a jumping spider
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Data from: GHOST: Recovering Historical Signal from Heterotachously-evolved Sequence Alignments
<p><span>Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE (</span><a class="link link-uri" href="http://www.iqtree.org/">http://www.iqtree.org</a><span>). Simulations show that using the GHOST model, IQ-TREE can accurately recover the tree topology, branch lengths, and substitution model parameters from heterotachously evolved sequences. We investigate the performance of the GHOST model on empirical data by sampling phylogenomic alignments of varying lengths from a plastome alignment. We then carry out inference under the GHOST model on a phylogenomic data set composed of 248 genes from 16 taxa, where we find the GHOST model concurs with the currently accepted view, placing turtles as a sister lineage of archosaurs, in contrast to results obtained using traditional variable rates-across-sites models. Finally, we apply the model to a data set composed of a sodium channel gene of 11 fish taxa, finding that the GHOST model is able to elucidate a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare inference under the GHOST model to partitioning by codon position and show that, owing to the minimization of model constraints, the GHOST model offers unique biological insights when applied to empirical data.</span></p>
HCV IVT 002 - Aligned Signals to HCV [Two Replicates]
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Data from: GHOST: Recovering Historical Signal from Heterotachously-evolved Sequence Alignments
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KLF2-induced actin shear fibers control both alignment to flow and JNK signaling in vascular endothelium
GEO Series GSE19412. Homo sapiens. 26 samples. Type: Expression profiling by array; Protein profiling by protein array.
Result data for article "Clade-wise alignment integration improves co-evolutionary signals for protein-protein interaction prediction"
<p>This dataset contains all the necessary data to reproduce figures in the paper [ "Clade-wise alignment integration improves co-evolutionary signals for protein-protein interaction prediction"](https://www.biorxiv.org/content/10.1101/2023.07.28.550005v1).</p> <p>More details can be found at: <a href="https://github.com/TaoDFang/PPI_Prediction_byCoevolution">https://github.com/TaoDFang/PPI_Prediction_byCoevolution</a></p>
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell
GEO Series GSE303560. Candida albicans SC5314. 20 samples. Type: Expression profiling by high throughput sequencing.
The effect of CPXM2-aligned collagen on gene expresssion and the intracellular signaling pathway in PaTu 8988t cells.
GEO Series GSE292740. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell [RNA004]
GEO Series GSE304703. synthetic construct. 4 samples. Type: Other.
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell [nanopore_DRS]
GEO Series GSE304702. Candida albicans; synthetic construct. 35 samples. Type: Other.
Zone Equalisation Normalisation For Improved Alignment of Epigenetic Signal
GEO Series GSE311157. Homo sapiens. 14 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Direct RNA sequencing and signal alignment reveal RNA structure ensembles in a eukaryotic cell
GEO Series GSE309111. synthetic construct. 8 samples. Type: Other.
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.