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opencc-by-4.0Nov 2023View details →

Plexcitonic Nanorattles as Highly Efficient SERS-Encoded Tags

Recent publication:  <h1>Plexcitonic Nanorattles as Highly Efficient SERS-Encoded Tags</h1> <div> </div> <div> <div> <div> <div><a href="https://onlinelibrary.wiley.com/authored-by/Est%C3%A9vez%E2%80%90Varela/Carla">Carla Estévez-Varela</a>, <a href="https://onlinelibrary.wiley.com/authored-by/N%C3%BA%C3%B1ez%E2%80%90S%C3%A1nchez/Sara">Sara Núñez-Sánchez</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Pi%C3%B1eiro%E2%80%90Varela/Paula">Paula Piñeiro-Varela</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Aberasturi/Dorleta+Jim%C3%A9nez">Dorleta Jiménez de Aberasturi</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Liz%E2%80%90Marz%C3%A1n/Luis+M.">Luis M. Liz-Marzán</a>, <a href="https://onlinelibrary.wiley.com/authored-by/P%C3%A9rez%E2%80%90Juste/Jorge">Jorge Pérez-Juste</a>, <a href="https://onlinelibrary.wiley.com/authored-by/Pastoriza%E2%80%90Santos/Isabel">Isabel Pastoriza-Santos</a></div> </div> </div> </div> <div> <div>First published: 27 November 2023</div> <div><a href="https://doi.org/10.1002/smll.202306045">https://doi.org/10.1002/smll.202306045</a></div> </div>   Abstract: Plexcitonic nanoparticles exhibit strong light-matter interactions, mediated by localized surface plasmon resonances, and thereby promise potential applications in fields such as photonics, solar cells, and sensing, among others. Herein, these light-matter interactions are investigated by UV-visible and surface-enhanced Raman scattering (SERS) spectroscopies, supported by finite-difference time-domain (FDTD) calculations. Our results reveal the importance of combining plasmonic nanomaterials and J-aggregates with near-zero-refractive index. As plexcitonic nanostructures nanorattles are employed, based on J-aggregates of the cyanine dye 5,5,6,6-tetrachloro-1,1-diethyl-3,3-bis(4-sulfobutyl)benzimidazolocarbocyanine (TDBC) and plasmonic silver-coated gold nanorods, confined within mesoporous silica shells, which facilitate the adsorption of the J-aggregates onto the metallic nanorod surface, while providing high colloidal stability. Electromagnetic simulations show that the electromagnetic field is strongly confined inside the J-aggregate layer, at wavelengths near the upper plexcitonic mode, but it is damped toward the J-aggregate/water interface at the lower plexcitonic mode. This behavior is ascribed to the sharp variation of dielectric properties of the J-aggregate shell close to the plasmon resonance, which leads to a high opposite refractive index contrast between water and the TDBC shell, at the upper and the lower plexcitonic modes. This behavior is responsible for the high SERS efficiency of the plexcitonic nanorattles under both 633 nm and 532 nm laser illumination. SERS analysis showed a detection sensitivity down to the single-nanoparticle level and, therefore, an exceptionally high average SERS intensity per particle. These findings may open new opportunities for ultrasensitive biosensing and bioimaging, as superbright and highly stable optical labels based on the strong coupling effect.

opencc-by-4.0Jan 2024View details →

Dataset of Social buffering switches fear to safety encoding by oxytocin recruitment of central amygdala buffer neurons

Dataset of Hegoburu et al., Social buffering switches fear to safety encoding by oxytocin recruitment of central amygdala buffer neurons, Nature Communications. ABSTRACT The presence of a companion can reduce fear, but the precise neural mechanisms underlying this social buffering of fear (SBF) are incompletely known. We studied SBF in male and female rats, and its encoding in the amygdala of males, that were fear-conditioned (FC) to auditory conditioned stimuli (CS). Pharmacological, opto,- and/or chemogenetic interventions showed that oxytocin (OT) signaling from hypothalamus-to-central amygdala (CeA) projections was required for acute fear reduction in the presence, and SBF retention 24h later without the companion. Single-unit recordings with optetrodes revealed fear-encoding CeA neurons (characterized by increased CS-responses after FC) were inhibited by SBF and blue light (BL) stimulation of OTergic projections. Other CeA neurons increased CS responses only after SBF exposure. Their baseline activity was enhanced by BL and exposure to the companion. SBF thus switches the CS from encoding "fear" to "safety" by OT-mediated recruitment of a distinct group of CeA "buffer neurons".

FASTA file containing to the MYB encoding gene Ant1 genomic sequences corresponding to wild and cultivated tomato accessions

Fasta sequence correspond to the MYB encoding gene An2-like. The genomic sequences correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome, and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>).

FASTA file containing the MYB encoding gene An2-like genomic sequences corresponding to wild and cultivated tomato accessions

FASTA sequence corresponds to the MYB encoding gene An2-like. The genomic sequences correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome (Hosmani et al., 2019), S. lycopersicum variety Indigo Rose (Yan et al., 2020), S. lycopersicum accession LA1996 [MN242011.1 (Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018),  Indigo Rose [MN433087 (Yan et al., 2020)], S. lycopersicum accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI)(available at NCBI: <a href="https://www.ncbi.nlm.nih.gov">https://www.ncbi.nlm.nih.gov</a>).

FASTA file containing the MYB encoding genes at the Aft locus with genomic sequences corresponding to wild and cultivated tomato accessions

FASTA sequences correspond to the MYB encoding genes An2-like and Ant1. The genomic sequences were combined correspond to Solanum galagpagnese accession LA1141 (this study), S. lycopersicum variety OH8245 (this study), S. lycopersicum variety Heinz 1706 reference genome (Hosmani et al., 2019), LA1996 [MN242011.1, EF433417.1(Sapir et al., 2008; Colanero et al., 2020)], and 84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Local sequences databases were made and retrieved using BLAST version/2018-08 for 84 accessions from The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences corresponding to Heinz 1706 (Hosmani et al., 2018), S. lycopersicum accession LA1996 [MN242011.1, EF433417.1 (Sapir et al., 2008; Colanero et al., 2020)], S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)] were accessed using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at <a href="https://solgenomics.net/tools/blast/">https://solgenomics.net/tools/blast/</a>) and the National Center for Biotechnology Information (NCBI) (available at NCBI: <a href="https://www.ncbi.nlm.nih.gov/">https://www.ncbi.nlm.nih.gov</a>).

opencc-by-4.0Jun 2024View details →

Synthetic datasets reflecting the shRNA-seq knockdown ENCODE data for HepG2 and K562 with coresponding GRN

Synthetic data correspond to the ENCODE data for cell lines HepG2 (https://www.encodeproject.org/biosamples/ENCBS282XVK/) and K562 (https://www.encodeproject.org/biosamples/ENCBS023XVB/). The data and networks were generated using GeneSPIDER (publicly available at https://bitbucket.org/sonnhammergrni/genespider/).   Table.1 Description of the files <table> <tbody> <tr> <td>data_HepG2like_SNR_L=0.0054699_diff=1.6188e-05.txt</td> <td>Synthetic gene expression knockdown (shRNA-seq) data immitating the ENCODE data for HepG2 cell line. Data size: 232 RBPs vs 464 experiments (2 replicates). SNR_L is the value of signal to noise ratio. Difference (diff) value tells the difference between replicate correlation coefficients of real and synthetic ENCODE data. Columns represent experiments, rows represent genes.</td> </tr> <tr> <td>data_K562like_SNR_L=0.0028692_diff=0.00017339.txt</td> <td>Synthetic gene expression knockdown (shRNA-seq) data immitating the ENCODE data for K562 cell line. Data size: 232 RBPs vs 464 experiments (2 replicates). SNR_L is the value of signal to noise ratio. Difference (diff) value tells the difference between replicate correlation coefficients of real and synthetic ENCODE data. Columns represent experiments, rows represent genes.</td> </tr> <tr> <td>network_HEPG2like_sparsity4.txt</td> <td>Synthetic scale-free gene regulatory network compatibile with data_HepG2like_SNR_L=0.0054699_diff=1.6188e-05.txt. Sparsity (average node degree) is 4 including selfloops. Direction should be read from columns to rows.</td> </tr> <tr> <td>network_K562like_sparsity4.txt</td> <td>Synthetic scale-free gene regulatory network compatibile with data_K562like_SNR_L=0.0028692_diff=0.00017339.txt. Sparsity (average node degree) is 4 including selfloops. Direction should be read from columns to rows.</td> </tr> <tr> <td>perturbations_HepG2&K562_2replicates.txt</td> <td>Perturbation matrix including information about knockeddown RBPs. Data size: 232 RBPs vs 464 experiments (2 replicates).</td> </tr> </tbody> </table>   Created by Garbulowski et al. (2024) as a part of the work entitled "Comprehensive analysis of the RBP regulome reveals functional modules and drug candidates in liver cancer"

opencc-by-4.0Apr 2023View details →

Beethoven in the House: Selective Encodings of Arrangements of Beethoven's opp. 91, 92, and 93.

This dataset contains selective MEI encodings of a number of arrangements of Beethoven's Opp. 91, 92, and 93. These encodings were prepared in the context of the Beethoven in the House project, jointly funded by AHRC and DFG from 2020 to 2023. It is a slight update on v1.0.0 in better organizing the release assets.

opencc-by-nc-nd-4.0May 2023View details →

Image sets used in the development of a connected auto-encoders based approach to separate mixed X-radiographs from double-sided paintings

The following sets of images were used during the development of an algorithm (described in the publication detailed below) designed to separate the mixed X-radiographs from double-sided paintings into two hypothetical X-ray images corresponding to each side of the painting, when visible images of the two sides of the painting are available. The images sets are taken from a painting that is only painted on one side and were used to assess the regularization parameters associated with the separation approach. The details are taken from the visible image and the X-radiograph of Anthony van Dyck’s painting Lady Elizabeth Thimbelby and Dorothy, Viscountess Andover dated to about 1635 and now in the collection of the National Gallery in London (NG6437). See <a href="https://www.nationalgallery.org.uk/paintings/anthony-van-dyck-lady-elizabeth-thimbelby-and-her-sister">https://www.nationalgallery.org.uk/paintings/anthony-van-dyck-lady-elizabeth-thimbelby-and-her-sister</a> for further details of the painting. The code can be downloaded from: <a href="https://github.com/ART-ICT/Xray_Separation_2RGB">https://github.com/ART-ICT/Xray_Separation_2RGB</a> and the algorithm is described in W. Pu, B. Sober, N. Daly, C. Zhou, Z. Sabetsarvestani, C. Higgitt, I. Daubechies and M. Rodrigues, ‘Image Separation with Side Information: A Connected Auto-Encoders Based Approach’, Transactions on Image Processing, 2023  All images © The National Gallery, London   Datasets available: NG6437_vis_800pixel_230502.tif: 800 pixel thumbnail visible image of the entire painting showing the location of the two details used for the algorithm development. This image is derived from a visible image of the whole painting acquired 25 November 2019 (Original file: N-6437-00-000041.tif; 6272 x 5940 pixels). NG6437_xray_800pixel_230502.tif: 800 pixel thumbnail image of the X-radiograph of the entire painting showing the location of the two details used for the algorithm development. This image is derived from the composite X-radiography of the whole painting created by mosaicking digital scans of the individual sheets of film and then registering the resulting image to the high resolution visible image described above (Original file: N-6437-00-000049.tif; 36847 x 32516 pixels). NG6437_vis_crop_01_230502.tif: 1543 x 2078 pixel detail taken from the high resolution visible image described above. NG6437_xray_crop_01_230502.tif:  1543 x 2078 pixel detail of the X-radiograph corresponding to NG6437_vis_crop_01_230502.tif. The X-ray images were acquired using sheets of film (27 November 2019) and 16-bit digital scans were then produced (original files: N-6437-00-000047-009 and -014 (each 9539 x 7199 pixels), processed 28 January 2020). This crop is an 8-bit composite image of 2 X-ray plates that had been manually registered to the high resolution visible image described above using Adobe Photoshop. NG6437_vis_crop_02_230502.tif: 1562 x 2023 pixel detail taken from the high resolution visible image described above. NG6437_xray_crop_02_230502.tif:  1543 x 2078 pixel detail of the X-radiograph corresponding to NG6437_vis_crop_02_230502.tif. The X-ray images were acquired using sheets of film (27 November 2019) and 16-bit digital scans were then produced (original files: N-6437-00-000047-002 and -007 (each 9539 x 7199 pixels), processed 28 January 2020). This crop is an 8-bit composite image of 2 X-ray plates that had been manually registered to the high resolution visible image described above using Adobe Photoshop. NG6437_vis_crop_03_230502.tif: 2088 x 2088 pixel detail taken from the high resolution visible image described above. NG6437_xray_crop_03_230502.tif:  2088 x 2088 pixel detail taken from the composite X-radiograph described above corresponding to NG6437_vis_crop_03_230502.tif.  NG6437_vis_crop_04_230502.tif: 2088 x 2088 pixel detail taken from the high resolution visible image described above. NG6437_xray_crop_04_230502.tif:  2088 x 2088 pixel detail taken from the composite X-radiograph described above corresponding to NG6437_vis_crop_04_230502.tif.

OpenNeuro44/100

Somatosensory phase-encoded bilateral full-body light touch stimulation

Open the record for dataset details and reuse information.

openCC0Jan 2020View details →

opencc-by-4.0Aug 2019View details →

Temporal super-resolution microscopy using a hue-encoded shutter

This dataset contains the data to reproduce the figures in our paper called "Temporal super-resolution microscopy using a hue-encoded shutter", Biomedical Optics Express, 2019. Together with the data, the code is available on <a href="https://github.com/idiap/hesm_distrib">Idiap's GitHub page</a>.

opencc-by-4.0Jul 2020View details →

Towards a generic processingand presentation ofTEI encoded digital editions

This dataset is the basis for the talk given at the TEI Member's Meeting 2014, Evanston, IL The abstract of the paper submitted: The set of XSL stylesheets provided and maintained by the TEI is relatively cautious about processing and presentation of transcriptions and content of digital editions. Only very basic functions are implemented, such as to surround abbreviations with brackets or to process from the element choice in plain mode only those children that represent the "critical" reading. Processing in plain mode means that the elements will be treated as in-line elements.[1] On the other hand the encoding must have been done with a special purpose. A general rule of text encoding is that the editor may encode only those structures and semantic features that he wants to process in the end. The processing might include elaborated examination and analysis of the encoded text or more complex queries as well as a reproduction of visual properties of the original document or provide a (simplified) reading text. Thus the encoding will tell something about the functionalities of the text in processing and presentation. According to Patrick Sahle's "Textrad"[2], "the" text does not exist in a transcription but the encoded text usually represents multiple properties and serves multiple purposes. Whatever the editor might state in some introductory notes and the documentation of the edition which should contain some statements about the encoding used, in the end the encoded text will speak on its own, can be interpreted and will be processed as is. In succession of the modelling of the TEI, realised in the modules, the grouping of elements and of attributes, the semantics of certain elements might let the processor estimate about the foreseen presentation, processing, and use: - The elements <pb>, <lb>, <l>, <lg>, etc. as well as attributes @rend, @rendition or @style represent visual aspects of the text, therefore these might have to be reproduced; users may be given a choice to either see a document-centred view which visualises these aspects or switch to an editorial view on the text which eliminates these properties. - The same applies to the element <choice>: If this is used the editor must have had in mind the opportunity to change the views on the document respectively encoded text. - Entities encoded as <rs>, <name>, <persName>, <placeName>, etc might be referenced, especially if they are accompanied by the related list elements such as <listPerson>, <listPlace>, etc. Additionally, one might assume that there will be norm data available which allows for links into the open. - Bibliographic records (<bibl>, <msDesc>) will serve a similar purpose and will have to be referenced. - Quotations like <cit>, <foreign>, <q>, <quote> etc. will have to be distinguished from the surrounding text. Concerning the overall structure of an (critical) edition one might expect up to three apparatuses: The critical apparatus, the commentary and maybe a bibliographical apparatus. How many of these are present in a given edition is up to the editor but the presence of certain elements and especially of the amount of certain elements will give anybody an idea of how many apparatuses are "appropriate": If the encoding contains editorial elements like <choice>, <abbr>/<expan>, <add>/<del>, etc. the representation of this information in an apparatus will be inevitable. If a certain amount of bibliographic references point to biblical or classical texts the tradition of the publication of editions has provided a separate apparatus as well. Last, editorial notes will have to be distinguished from the former two categories. This paper will examine existing editions with statistical methods and by clustering the elements used it might be possible to assign the encoded text to one or more text types of Sahle's typology. Additionally, the paper shall foster the discussion about the presentation of an edited text according to the intended purpose of the encoding. On the basis of the typology and purpose of the edition it will be more likely that a generic presentation of any edited text is possible. Finally, with some statistical data about the editions some remarks about the interoperability of the TEI-encoded texts shall be possible. [1] e.g. https://github.com/TEIC/Stylesheets/blob/master/html/html_core.xsl [2] Patrick Sahle: Digitale Editionsformen, 3 vols. 2013, esp. vol. 3, p. 9ff.

opencc-by-4.0Jun 2023View details →

Challenges in Replay Detection by TDLM in Post-Encoding Resting State

Data for the paper "Challenges in Replay Detection by TDLM in Post-Encoding Resting State". This extension of the previous dataset contains the resting state data. For each participant, a 8 minutes resting state was recorded before and after the main experiment (localizer plus learning), and before the final retrieval session. Two files are uploaded per participant, the pre-experiment resting state (RS1) and the post-learning resting state (RS2). All files are MaxFiltered and the head positioning has been realigned using MaxFilter movement correction to the head position during the initial localizer. The localizer data has been previously published and can be downloaded in v1 of this dataset at https://doi.org/10.5281/zenodo.8001755 All relevant information can be found in the related publication. Behavioural data necessary to reproduce the results will be uploaded to GitHub at https://github.com/CIMH-Clinical-Psychology/DeSMRRest-TDLM-Simulation There are markers in the files as follows: ############################################################### ## Port Trigger Table ## Port Code | Meaning ## --------------------------------------------------- ## 0      | don't send trigger ## 10         | start RS session ## 11         | end RS session ## 127    | button press has happened ## 255    | start and end of session ###############################################################

FASTA file containing the MYB encoding gene An2-like and Ant1 coding sequences corresponding to wild and cultivated tomato accessions

The coding sequence (CDS) of the MYB encoding genes Ant1 and An2-like. Sequences were retrieved from regions corresponding to the Aft locus from Solanum galapagense accession LA1141, S. lycopersicum variety OH8245, and  84 tomato accessions published as part of The 100 Tomato Genome Sequencing Consortium (The 100 Tomato Genome Sequencing Consortium et al., 2014). Sequences were compared to available CDS available from the Sol genomics network (SGN) and the National Center for Biotechnology Information. The CDS was retrieved from S. lycopersicum variety Indigo Rose [MN433087 (Yan et al., 2020)], S. lycopersicum accession LA1996 [MN242011.1, EF433417.1( Sapir et al., 2008; Colanero et al., 2020)], and S. chilense accession LA1930 [MN242012.1 (Colanero et al., 2020)], The orthologous CDS corresponding to the Aft MYB encoding genes from Solanum tuberosum L. Group Phureja clone DM1-3 genome (PGSC DM v4.03 Pseudomolecules) was retrieved from the Potato Genome Sequence Consortium (PGSC: Potato Genome Sequencing Consortium et al., 2011), and the Capsicum annum cv. CM334 genome was retrieved from Capsicum annuum cv CM334 genome chromosome release 1.55 (Hulse-Kemp et al. 2018). These CDS were obtained using the Basic Local Alignment Search Tool (BLAST) tool available from the Sol Genomics Network (SGN) (available at https://solgenomics.net/tools/blast/). Comparison of syntenic chromosomal regions using known positions of tomato, potato, and pepper markers with comparative map viewer from  SGN: (available at https://solgenomics.net/cview) on chromosome 10, was used as a quality check for S. tuberosom and C. annuum. Orthologous CDS corresponding to Salvia miltiorrhiza, Arabidopsis thaliana, [NM_105308.2, NM_105310.4 (Teng et al., 2005, Cominelli et al., 2008; Beradini et al., 2015)] were chosen based on tomato Aft sequence homology and gene annotations of positive R2R3 MYB regulation of anthocyanin. The CDS corresponding to the Aft genes were retrieved from the CDS reference genomes available from the Sol Genomics Network SGN: Tomato Genome CDS (ITAG release 4.0), Potato PGSC DM v3.4 CDS sequences, Capsicum annuum cv CM334 Genome CDS (release 1.55), or from the National Center for Biotechnology Information (NCBI: https://www.ncbi.nlm.nih.gov) reference sequences (RefSeq) section of the Genbank records. When accessed from Genank records, the CDS sequence was extracted from the “features” section and exported as a FASTA file.

opencc-by-4.0Jan 2022View details →

Data for Scalable parametric encoding of multiple modalities

Two folders with figures created using Generative Encoding, using data from Stenbeck et al [1]:   Folder 1 - epithelial_immune_transition This contains in-silico perturbations of epithelial and immune genes. Using generative encoders, the transformation begins with a histology to gene expression transformation, a perturbation of the gene expression vector, followed by an inverse transformation back to histology.   Folder 2 - heatmap_he_et_al This contains in-silico transformation of histology tissue to gene expression. It is similar to the first folder, yet is only a single transformation (without an inverse) from histology to gene expression.     [1] Stenbeck, Linnea; Bergenstråhle, Ludvig; Lundeberg, Joakim; Borg, Åke (2021), “Human breast cancer in situ capturing transcriptomics”, Mendeley Data, V5, doi: 10.17632/29ntw7sh4r.5

opencc-by-4.0Dec 2021View details →

Principles of gait encoding in the subthalamic nucleus of people with Parkinson's disease

Disruption of subthalamic nucleus dynamics in Parkinson’s disease leads to impairments during walking. Here, we aimed to uncover the principles through which the subthalamic nucleus encodes functional and dysfunctional walking in people with Parkinson’s disease.  We conceived a neurorobotic platform embedding an isokinetic dynamometric chair that allowed us to deconstruct key components of walking under well-controlled conditions. We exploited this platform in 18 patients with Parkinson’s disease to demonstrate that the subthalamic nucleus encodes the initiation, termination, and amplitude of leg muscle activation. We found that the same fundamental principles determine the encoding of leg muscle synergies during standing and walking. We translated this understanding into a machine learning framework that decoded muscle activation, walking states, locomotor vigor, and freezing of gait. These results expose key principles through which subthalamic nucleus dynamics encode walking, opening the possibility to operate neuroprosthetic systems with these signals to improve walking in people with Parkinson’s disease.

opencc-by-4.0Jul 2022View details →

TriCera Benchmarks: SMT-LIB Encodings of SV-COMP 2022 Benchmarks by TriCera

This repository contains the SMT-LIB v2.6 encodings of a subset of SV-COMP 2022 benchmarks from the reach-safety and the memsafety categories, encoded by <a href="https://github.com/uuverifiers/tricera">TriCera</a> and <a href="https://github.com/zafer-esen/heap2array">heap2array</a> [1, 2]. The source benchmarks from SV-Comp 2022 (`.c` and `.i` files together with their accompanying `.yml` files) are not provided due to licensing reasons; the files are freely available for download at <a href="https://zenodo.org/record/5831003/export/hx">https://zenodo.org/record/5831003/export/hx</a> - `benchmarks/heap` contains all heap benchmarks (encoded by TriCera using the <a href="https://arxiv.org/abs/2104.04224">theory of heaps</a>, used in [1] and [2]). - `benchmarks/heap2array` contains all heap2array encoded benchmarks (encoded from heap benchmarks using heap2array, used in [1] and [2]). - `benchmarks/nonHeapBms` contains all non-heap benchmarks (encoded by TriCera, used in [2]). [1] (to appear) Zafer Esen and Philipp Rümmer, "An SMT-LIB Theory of Heaps", SMT 2022 [2] (to appear) Zafer Esen and Philipp Rümmer, "TriCera: Verifying C Programs Using the Theory of Heaps", FMCAD 2022

opencc-by-4.0Apr 2024View details →

A complete map of specificity encoding for a partially fuzzy protein interaction

All data required to run analyses for "A complete map of specificity encoding for a partially fuzzy protein interaction". Please see <a href="https://github.com/lehner-lab/fuzzy_specificity">https://github.com/lehner-lab/fuzzy_specificity</a> for instructions.

opencc-zeroApr 2019View details →

Bohdan-Khomtchouk/ENCODE_TF_geneXtendeR_analysis: ENCODE_TF_geneXtendeR_analysis

geneXtendeR analysis on 547 ENCODE ChIP-seq datasets for both proximal and distal transcription factor (TF) binding peaks for all cell types used in <a href="https://bioconductor.org/packages/geneXtendeR/">https://bioconductor.org/packages/geneXtendeR/</a>.