Our Work

Supplementary Material for "Flügel et al.: Chebifier 2: An Ensemble for Chemistry" (in submission). This includes the dataset used (3-STAR and full-ChEBI variants), model checkpoints, hyperparame…

Supplementary Material for "Flügel et al.: Chebifier 2: An Ensemble for Chemistry" (in submission). This includes the dataset used (3-STAR and full-ChEBI variants), model checkpoints, hyperparameters and test set predictions for the evaluated aggregation and resolution methods.

This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.

This repository contains the research data and R analysis scripts associated with a study investigating the direct antagonistic activity and plant-mediated protective effects of endophytic microorgani…

This repository contains the research data and R analysis scripts associated with a study investigating the direct antagonistic activity and plant-mediated protective effects of endophytic microorganisms isolated from wild grapevine against Botrytis cinerea. The repository includes machine-readable datasets and reproducible R scripts for the analysis of indole-related compound production, mineral solubilization, in vitro antagonism, bacterial growth kinetics, ACC utilization, PEG 6000-induced osmotic stress, grapevine disease severity, culturable bacterial populations, and defence-related gene expression by qPCR. Files are organized into data/ and scripts/ directories. Each script automatically creates the corresponding output/ directory and generates the associated statistical results, tables, and figures when executed. The deposited materials support the reproducibility of the analyses reported in the associated manuscript.

Mazkur maqolada zamonaviy ta’lim jarayonida o‘qituvchilarning axborot-kommunikatsiya texnologiyalaridan samarali foydalanish malakalarini shakllantirish masalalari yoritilgan. Ta’lim…

Mazkur maqolada zamonaviy ta’lim jarayonida o‘qituvchilarning axborot-kommunikatsiya texnologiyalaridan samarali foydalanish malakalarini shakllantirish masalalari yoritilgan. Ta’lim sifatini oshirishda raqamli texnologiyalarning o‘rni, pedagoglarning raqamli kompetensiyasini rivojlantirishning asosiy yo‘nalishlari, elektron ta’lim resurslari, interaktiv platformalar, multimedia vositalari va sun’iy intellekt imkoniyatlaridan foydalanish masalalari tahlil qilingan. Shuningdek, o‘qituvchilarning zamonaviy axborot texnologiyalaridan foydalanish ko‘nikmalarini rivojlantirishning pedagogik shart-sharoitlari va amaliy usullari bayon etilgan.

Maqolada tijorat banklarida likvidlik siyosatini optimallashtirish masalasi Basel III standartlari asosida tahlil qilingan. Likvidlilikni qoplash me'yori (LCR) va sof barqaror moliyalashtirish me'yori…

Maqolada tijorat banklarida likvidlik siyosatini optimallashtirish masalasi Basel III standartlari asosida tahlil qilingan. Likvidlilikni qoplash me'yori (LCR) va sof barqaror moliyalashtirish me'yori (NSFR) dinamikasi orqali bank tizimining qisqa va uzoq muddatli barqarorligi baholangan. Tadqiqot natijalari likvidlikni boshqarishning ilg'or mexanizmlari, jumladan, diversifikatsiya, stress-testlash hamda aktivlar va passivlar mosligini ta'minlash bank moliyaviy barqarorligini mustahkamlashda muhim ahamiyatga ega ekanini ko'rsatadi.

Maximum likelihood estimation of landscape conductance surfaces from genetic data on raster graphs, using Newton and quasi-Newton optimization with analytic derivatives. Fits log-linear conductance mo…

Maximum likelihood estimation of landscape conductance surfaces from genetic data on raster graphs, using Newton and quasi-Newton optimization with analytic derivatives. Fits log-linear conductance models with optional joint estimation of Gaussian smoothing scales and spline response shapes, linked to pairwise genetic distances through maximum likelihood population effects models or to allele-frequency covariance through a Wishart likelihood on site contrasts, with the same pairwise distance and environment covariates available in both. Provides exact sparse and algebraic multigrid solvers for large rasters, fixed-domain spatial cross-validation for comparing conductance formulas, and simulation tools for study design. Works natively with 'terra' objects.

Changes: Document per-particle species inputs and validation rules in Line.build_particles. Clarify that normalized coordinates require one species per call, including when W_matrix or R_matrix is su…

Changes: Document per-particle species inputs and validation rules in Line.build_particles. Clarify that normalized coordinates require one species per call, including when W_matrix or R_matrix is supplied. Document building each species separately and combining the results with Particles.merge. Full Changelog: https://github.com/xsuite/xtrack/compare/v0.115.4...v0.115.5

This data set contains thermographic images for the visualisation of watermarks. An IRCAM Equus 327k with Watermark Imager software (Fraunhofer) version 8.416 (R2016b) was used.

PanRes is a structure-informed antimicrobial resistance database that integrates resistance genes, protein translations, predicted protein structures, structure-based clusters, multiple sequence align…

PanRes is a structure-informed antimicrobial resistance database that integrates resistance genes, protein translations, predicted protein structures, structure-based clusters, multiple sequence alignments, and 3D-based Hidden Markov Models.  The database can also be explored through the PanRes web service: https://panres.rambio.dk/  PanRes (version 2.1.0) includes the following files: File Description panres_genes.fa FASTA file containing nucleotide sequences of PanRes genes. panres_proteins.faa FASTA file containing translated protein sequences. PanGenes.tsv Metadata table for PanRes genes, including database origin and ontology relationships. PanProteins.tsv Metadata table for PanRes proteins, including links to genes, clusters, and structures where available. PanStructures.tsv Metadata table for predicted structures and structure-cluster membership. README_metadata.md Description of the metadata tables. panres_ontology.owl OWL ontology file describing the PanRes data model and relationships. README_ontology.md Description of the PanRes ontology, including the main classes, object properties and annotation fields. PDBs.zip Predicted AlphaFold protein structures in PDB format, for example PAN1_struct.pdb. MSAs.zip Multiple sequence alignments for PanStructureClusters, used to build the HMM profiles, for example PANCL1_struct.full.aln.fasta. HMMs.zip Profile Hidden Markov Models for PanStructureClusters, for example PANCL1_struct.hmm. Changes in PanRes v2.1.0 Structures with low-confidence predictions (mean pLDDT < 70) were removed Singleton structural clusters containing these predictions were removed Corresponding HMMs were removed  Ontology was updated with DiscardedPanStructure and DiscardedPanStructureCluster classes  Metadata tables were updated to reflect the filtering A number of previously published collections of AMR genes were used in the creation of the original PanRes gene collection bundled with ARGprofiler(See references): ResFinder (downloaded 2023-01-20, (Bortolaia et al. 2020)), ResFinderFG (version 2.0, (Gschwind et al. 2023)) CARD (version 3.2.5, (Alcock et al. 2023)) MegaRes (version 3.0.0, (Bonin et al. 2023)) AMRFinderPlus (version 3.11/2022-12-19.1, (Feldgarden et al. 2021)) ARGANNOT (V6_July2019, (Gupta et al. 2014)) The 'CsabaPal' collection (Provided by Csaba Pál and Zoltán Farkas in November 2022, Daruka et al. 2023)) BacMet (version 1.1, (Pal et al. 2014))