S.S, Ashwin · Minami, Katsuhiko · Nakazato, Kako

11 files · 124 MB · jpeg, torch, zipdeclared

Supplementary code for: Katsuhiko Minami, Kako Nakazato, Sachiko Tamura, S. S. Ashwin, Kazuhiro Maeshima* Machine learning-assisted Repli-Histo labeling reveals distinct transcription-dependent constraints on chromatin motion in living cells (2026).

Pastor Durántez, Eduardo · Diez Casero, Julio Javier

2 files · 15 MB · gffdeclared

Curated, high-confidence structural gene annotation of Phytophthora plurivora (strain TJ71), provided in GFF3 format (15,415 gene models; gene, mRNA, exon, and CDS features). The annotation was generated with a BRAKER3-based structural prediction pipeline, followed by a custom curation workflow combining transcript deduplication, repeat- and expression-aware filtering, a heuristic homology-and-topology scoring scheme, and directed manual curation. This dataset was produced as part of the associated manuscript describing the genome annotation and two-speed genome architecture of P. plurivora . This annotation is built on the previously published genome assembly available at NCBI GenBank under accession ASM3002794v1. The genome FASTA itself is not included in this deposit. See the accompanying README.txt for full file description, methods summary, and locus tag conventions.

Gupte, Nihar · Miller, M. Coleman · Udall, Rhiannon · et al.

36 files · 36 GB · hdf5, torchdeclared

Data release for the DINGO O4a eccentricity paper. It contains the per-event parameter-estimation products, population selection function, and hierarchical-inference posteriors needed to reproduce every figure, table, and number in the paper, plus the trained DINGO neural networks used for the analyses. Event data : eccentric, quasicircular, and precessing per-event posterior samples (posteriors_eccentric.h5, posteriors_quasicircular.h5, posteriors_precessing.h5); slimmed log-uniform-eccentricity-prior posteriors used as the hierarchical-likelihood input (posteriors_log_uniform_eccentric.h5); per-event posteriors reweighted by the population-informed posterior (posteriors_population_reweighted.h5); per-event summary statistics with pre-computed Bayes factors (summary_statistics.h5); e_gw conversions (egw_conversions.h5); and the eccentricity-mean-anomaly prior hull (e_zeta_prior_hull.h5). Selection function : the injection p_draw dataframe with detection probabilities including the analysis-window factor (injection_p_draw.h5), a fixed-injection eccentricity sweep (fixed_injection_ecc_sweep.h5), and matched-filter survival-function data (survival_function.h5). Hierarchical inference : the selection-corrected velocity-dispersion posterior marginalized over the GWTC-4 mass/spin/redshift hyperposterior (sigma_posterior.h5), the capture-eccentricity lookup table (capture_ecc_table.h5), the external GWTC-4 hyperposterior fit (gwtc4_hyperposterior.h5), and the GC/NSC branching-fraction posterior (branching_fraction_posterior.h5). Glitch analyses : glitch-marginalized posteriors for GW190701, GW231114_043211, and GW231223_032836. Networks : trained DINGO networks (SEOBNRv5EHM, SEOBNRv5HM, SEOBNRv5PHM) with their training settings; see MODEL_MANIFEST.md. Zenodo stores files flat; the companion code maps each file into the foldered layout the notebooks expect. Code to download the data and reproduce all figures: github.com/nihargupte-ph/o4a-eccentricity , archived at doi:10.5281/zenodo.21221948 .

Kusza, Szilvia · Astuti, Putri Kusuma

1 files · 6.5 MB · vcfdeclared

Liu, Licheng

2 files · 5.2 MB · torchdeclared

Khalid, Adnan

1 files · 129 KB · torchdeclared