cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14661301
title: A curriculum learning approach to training antibody language models

description: Motivation. There is growing interest in antibody language models (AbLMs) being pre-trained with a mixture of unpaired and natively paired sequencing data. This is due to the proven benefits of pre-training with natively paired sequences, but their relative sparity compared to unpaired data. Existing models trained with unpaired and paired data typically use a finetuning approach to pre-training, but this can result in catastrophic forgetting of the unpaired sequences. We explore if a curriculum learning approach to pre-training could help address these issues.

Results. We introduce a modified version of curriculum learning for training AbLMs, to modify the sampling of training data throughout training. This results in a gradual transition from unpaired to paired data throughout training. We optimize this approach and observe that our 650M-parameter curriculum model, CurrAb, outperforms existing AbLMs in downstream classification tasks.

Files. The following files are included in this repository:



CurrAb.tar.gz: Model weights for the CurrAb model. Model can also be downloaded from HuggingFace.

TTE_paired-downsampled.tar.gz: Downsampled paired datasets used to train, test, and evaluate the 55M parameter models.

TTE_unpaired-downsampled.tar.gz: Downsampled unpaired datasets used to train, test, and evaluate the 55M parameter models.

TTE_paired-full.tar.gz: Full paired datasets used to train, test, and evaluate the 650M parameter models including CurrAb.

TTE_unpaired-full.tar.gz: Full unpaired datasets used to train, test, and evaluate the 650M parameter models including CurrAb.

classification-datasets.tar.gz: Three classification datasets used to train classification models in Figure 5. The datasets are: flu-0_cov-1.csv, hd-0_cov-1.csv, and hd-0_flu-1_cov-2.csv. CoV antibody sequences were obtained from CoV-AbDab, Flu antibody sequences were obtained from Wang et al., and healthy donor antibody sequences were obtained from Jaffe et al. and Phad et al.


Code: The code for model training and evaluation is available under the MIT license on GitHub.
DOI: 10.5281/zenodo.14661302
title: A curriculum learning approach to training antibody language models

description: Motivation. There is growing interest in antibody language models (AbLMs) being pre-trained with a mixture of unpaired and natively paired sequencing data. This is due to the proven benefits of pre-training with natively paired sequences, but their relative sparity compared to unpaired data. Existing models trained with unpaired and paired data typically use a finetuning approach to pre-training, but this can result in catastrophic forgetting of the unpaired sequences. We explore if a curriculum learning approach to pre-training could help address these issues.

Results. We introduce a modified version of curriculum learning for training AbLMs, to modify the sampling of training data throughout training. This results in a gradual transition from unpaired to paired data throughout training. We optimize this approach and observe that our 650M-parameter curriculum model, CurrAb, outperforms existing AbLMs in downstream classification tasks.

Files. The following files are included in this repository:



CurrAb.tar.gz: Model weights for the CurrAb model. Model can also be downloaded from HuggingFace.

TTE_paired-downsampled.tar.gz: Downsampled paired datasets used to train, test, and evaluate the 55M parameter models.

TTE_unpaired-downsampled.tar.gz: Downsampled unpaired datasets used to train, test, and evaluate the 55M parameter models.

TTE_paired-full.tar.gz: Full paired datasets used to train, test, and evaluate the 650M parameter models including CurrAb.

TTE_unpaired-full.tar.gz: Full unpaired datasets used to train, test, and evaluate the 650M parameter models including CurrAb.

classification-datasets.tar.gz: Three classification datasets used to train classification models in Figure 5. The datasets are: flu-0_cov-1.csv, hd-0_cov-1.csv, and hd-0_flu-1_cov-2.csv. CoV antibody sequences were obtained from CoV-AbDab, Flu antibody sequences were obtained from Wang et al., and healthy donor antibody sequences were obtained from Jaffe et al. and Phad et al.


Code: The code for model training and evaluation is available under the MIT license on GitHub.
DOI: 10.7910/dvn/fdafnz
title: National Health and Nutrition Examination Survey (NHANES), 1999-2023

description: [Data pulled on January 31, 2025]: Folder contains all continuous NHANES data from the 1999-2000 to the 2021-2023 cycles, except the raw 80z physical activity data and the ambient light raw data, which are ~1TB per year.
DOI: 10.15468/dl.dq52ku
title: Occurrence Download

description: A dataset containing 390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quercus oblongifolia Torr.)",
 "StateProvince is one of (Arizona, Mexico Northeast, Mexico Northwest, New Mexico, Texas)",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 390 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069020-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2f3c84
title: Occurrence Download

description: A dataset containing 25172 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lacerta agilis Linnaeus, 1758",
 "Country is Germany",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 25172 records from 122 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069021-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5v698r1d
title: MassIVE MSV000098322 - High-Throughput Screening of Amyloid Inhibitors via Covalent-Labeling Mass Spectrometry
title: MS spectra of DEPC modifications on b2m residues under amyloid-forming conditions, with or without 4-hydroxythalidomide.
DOI: 10.5281/zenodo.15740736
title: Accompanying data for the paper "Modeling of nonlinear viscoelasticity and stress softening in soft tissues"

description: Caro et al. (2025) – Supplementary Material 


This repository contains the Jupyter notebook used for the analyses presented in the paper:


Caro et al. (2025), Modeling of nonlinear viscoelasticity and stress softening in soft tissues https://dx.doi.org/10.2139/ssrn.5274578.


The dataset is identically stored on Zenodo and on Renkulab.


📓 Notebook


- Caro_et_al_2025.ipynb: Contains all code used for data processing, analysis, and figure generation related to the study.


🚀 Getting Started


You can run this notebook directly in Renkulab or in a local environment.


Run in Renkulab


Click the link below to launch the notebook in a pre-configured Renkulab session:
https://renkulab.io/p/sarah.iaquinta/supplementary-material-for-caro-et-al-2025



📂 Repository Contents


├── Caro_et_al_2025.ipynb   # Main analysis notebook

├── data/                   # Input data files

└── README.md               # Readme file


📈 Outputs


All figures and tables used in the manuscript are generated when running the notebook.


🔁 Reproducibility


The analysis is designed to be fully reproducible.


👩‍💻 Authors


- [Anne-Sophie Caro] – [anne-sophie.caro@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France

- [Andre Chrysochoos] – [andre.chrysochoos@umontpellier.fr] - LMGC, Univ Montpellier, CNRS, Montpellier, France

- [Sarah Iaquinta] – [sarah.iaquinta@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France

- [Grégory Chagnon] – [gregory.chagnon@univ-grenoble-alpes.fr] - Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France.

- Based on work by Caro et al. (2025)


📄 License


Creative Commons Attribution 4.0.


📄 Detailed description


This paper deals with the mechanical behavior of soft living tissues under

load-unload and relaxation cyclic strains. It proposes a thermodynamic model

formulated within the Generalized Standard Materials framework that incorporates

both Mullins’ effect and viscoelasticity, integrating the history dependent

behavior of the material under finite strain. A key innovation lies in the use of a

common softening function to modulate both the hyperelastic and viscous components,

capturing history-dependent behavior more accurately. Viscous parameters

are adjusted based on the loading history via the maximum strain invariant.

Numerical implementation is validated against uniaxial tensile tests on porcine

perineal tissues and a global Sobol sensitivity analysis confirms that elastic, viscous,

and Mullins-related parameters are identifiable from different phases of the

loading protocol. This model provides a unified, thermodynamical consistent tool

for simulating soft tissue mechanics.


Keywords: Soft tissue, Finite strain, Visco-hyperelasticity, Mullins effect,

Incompressibility
DOI: 10.5281/zenodo.15740737
title: Accompanying data for the paper "Modeling of nonlinear viscoelasticity and stress softening in soft tissues"

description: Caro et al. (2025) – Supplementary Material 


This repository contains the Jupyter notebook used for the analyses presented in the paper:


Caro et al. (2025), Modeling of nonlinear viscoelasticity and stress softening in soft tissues https://dx.doi.org/10.2139/ssrn.5274578.


The dataset is identically stored on Zenodo and on Renkulab.


📓 Notebook


- Caro_et_al_2025.ipynb: Contains all code used for data processing, analysis, and figure generation related to the study.


🚀 Getting Started


You can run this notebook directly in Renkulab or in a local environment.


Run in Renkulab


Click the link below to launch the notebook in a pre-configured Renkulab session:
https://renkulab.io/p/sarah.iaquinta/supplementary-material-for-caro-et-al-2025



📂 Repository Contents


├── Caro_et_al_2025.ipynb   # Main analysis notebook

├── data/                   # Input data files

└── README.md               # Readme file


📈 Outputs


All figures and tables used in the manuscript are generated when running the notebook.


🔁 Reproducibility


The analysis is designed to be fully reproducible.


👩‍💻 Authors


- [Anne-Sophie Caro] – [anne-sophie.caro@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France

- [Andre Chrysochoos] – [andre.chrysochoos@umontpellier.fr] - LMGC, Univ Montpellier, CNRS, Montpellier, France

- [Sarah Iaquinta] – [sarah.iaquinta@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France

- [Grégory Chagnon] – [gregory.chagnon@univ-grenoble-alpes.fr] - Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France.

- Based on work by Caro et al. (2025)


📄 License


Creative Commons Attribution 4.0.


📄 Detailed description


This paper deals with the mechanical behavior of soft living tissues under

load-unload and relaxation cyclic strains. It proposes a thermodynamic model

formulated within the Generalized Standard Materials framework that incorporates

both Mullins’ effect and viscoelasticity, integrating the history dependent

behavior of the material under finite strain. A key innovation lies in the use of a

common softening function to modulate both the hyperelastic and viscous components,

capturing history-dependent behavior more accurately. Viscous parameters

are adjusted based on the loading history via the maximum strain invariant.

Numerical implementation is validated against uniaxial tensile tests on porcine

perineal tissues and a global Sobol sensitivity analysis confirms that elastic, viscous,

and Mullins-related parameters are identifiable from different phases of the

loading protocol. This model provides a unified, thermodynamical consistent tool

for simulating soft tissue mechanics.


Keywords: Soft tissue, Finite strain, Visco-hyperelasticity, Mullins effect,

Incompressibility
DOI: 10.15468/dl.zw4nqc
title: Occurrence Download

description: A dataset containing 18170 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salamandra salamandra (Linnaeus, 1758)",
 "Country is Germany",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 18170 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069022-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gvx6dm
title: Occurrence Download

description: A dataset containing 1272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Acer saccharum Marshall",
 "Year 1910-1956"
 ]
}

 The dataset includes 1272 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069023-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.djqcfj
title: Occurrence Download

description: A dataset containing 1498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Croatia",
 "DatasetKey is iNaturalist Research-grade Observations",
 "TaxonKey is Mantodea"
 ]
}

 The dataset includes 1498 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069025-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7h9ucw
title: Occurrence Download

description: A dataset containing 2388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Musca domestica Linnaeus, 1758",
 "Country is Germany",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1990"
 ]
}

 The dataset includes 2388 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069024-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.48n69n
title: Occurrence Download

description: A dataset containing 3910 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "OccurrenceStatus is Present",
 "TaxonKey is Colaptes atricollis (Malherbe, 1850)"
 ]
}

 The dataset includes 3910 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069026-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2jnx26
title: CCDC 2343788: Experimental Crystal Structure Determination

description: Related Article: C. E. Shields, T. Fellowes, A. G. Slater, A. I. Cooper, K. G. Andrews, F. T. Szczypiński|2024|Chem.Commun.|60|6023|doi:10.1039/D4CC01407C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2jnx6b
title: CCDC 2343792: Experimental Crystal Structure Determination

description: Related Article: C. E. Shields, T. Fellowes, A. G. Slater, A. I. Cooper, K. G. Andrews, F. T. Szczypiński|2024|Chem.Commun.|60|6023|doi:10.1039/D4CC01407C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34770/envh-7358
title: Dataset for "Theory of zonal flow generation and propagation in toroidal geometry"

description: Dataset and input files to generate figures in "Theory of zonal flow
 generation and propagation in toroidal geometry."
DOI: 10.15468/dl.gmdw3m
title: Occurrence Download

description: A dataset containing 3583 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "OccurrenceStatus is Present",
 "TaxonKey is Spinus atratus (d'Orbigny & Lafresnaye, 1837)"
 ]
}

 The dataset includes 3583 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069027-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29310365
title: <b>Temperature Reshapes Viral Diversity in Subantarctic Chilean Patagonia Fjords</b>

description: Nucleotide (fna folder)<i> </i>and protein (faa folder) sequences of giant viruses (PolB) and bacteriophages generated in this study.
DOI: 10.6084/m9.figshare.29310365.v2
title: <b>Temperature Reshapes Viral Diversity in Subantarctic Chilean Patagonia Fjords</b>

description: Nucleotide (fna folder)<i> </i>and protein (faa folder) sequences of giant viruses (PolB) and bacteriophages generated in this study.
DOI: 10.6084/m9.figshare.29310365.v1
title: <b>Temperature Reshapes Viral Diversity in Subantarctic Chilean Patagonia Fjords</b>

description: Nucleotide (fna folder)<i> </i>and protein (faa folder) sequences of giant viruses (PolB) and bacteriophages generated in this study.
DOI: 10.6084/m9.figshare.29402411.v3
title: Data analysis

description: Python scripts used in this modules data analysis.
DOI: 10.15468/dl.586n6j
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quercus obtusata Bonpl.)",
 "StateProvince is one of (Mexico Central, Mexico Gulf, Mexico Northeast, Mexico Southwest)",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069029-250525065834625/datasets/export for details.
DOI: 10.15468/dl.ut7gyu
title: Occurrence Download

description: A dataset containing 614 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Sotalia guianensis (P.-J.van Bénéden, 1864)"
 ]
}

 The dataset includes 614 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069030-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15740962
title: Trajectories for G154D, P143T, M310L, Y178C, V171A
DOI: 10.5281/zenodo.15740963
title: Trajectories for G154D, P143T, M310L, Y178C, V171A
DOI: 10.15468/dl.pe87bu
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Quercus striatula Trel.)",
 "StateProvince is one of (Mexico Northeast)",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069032-250525065834625/datasets/export for details.
DOI: 10.15468/dl.497fma
title: Occurrence Download

description: A dataset containing 48937 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Acer saccharum Marshall",
 "Year 1980-2025"
 ]
}

 The dataset includes 48937 records from 191 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069031-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e75kf7
title: Occurrence Download

description: A dataset containing 1488 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "TaxonKey is Thomomys mazama Merriam, 1897"
 ]
}

 The dataset includes 1488 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013260-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5sch6w
title: Occurrence Download

description: A dataset containing 13939 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brosimum alicastrum Sw.",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 13939 records from 305 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013262-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dkk4ea
title: Occurrence Download

description: A dataset containing 406 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Heterodontus portusjacksoni (Meyer, 1793)"
 ]
}

 The dataset includes 406 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013263-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9n8faq
title: Occurrence Download

description: A dataset containing 342720 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is The Retrospective Analysis of Antarctic Tracking (Standardised) Data from the Scientific Committee on Antarctic Research",
 "TaxonKey is Leptonychotes weddellii (Lesson, 1826)"
 ]
}

 The dataset includes 342720 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013252-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zn6hkk
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Pleurothallis antennifera Lindl."
 ]
}

 The dataset includes 151 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013264-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m9e48h
title: Occurrence Download

description: A dataset containing 599 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Moscharia pinnatifida Ruiz & Pav."
 ]
}

 The dataset includes 599 records from 40 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013265-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.