2026-10-10T21:59:24Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33685081 2026-09-13T08:55:57Z category_24670 item_type_3 month_year_09_2026

ACA BYOL qPCR datasets and model checkpoints Louis Kreitmann (24844744) Medical biotechnology diagnostics (incl. biosensors) Amplification Curve Analysis single-channel multiplexing Asymmetric PCR Domain adaptation Self-supervised learning Molecular diagnostics TaqMan qPCR <p dir="ltr">Associated manuscript</p><p dir="ltr">Stoichiometric encoding of amplification kinetics enables high-level multiplexing in single-channel TaqMan real-time PCR</p><p dir="ltr">Louis Kreitmann, Kenny Malpartida-Cardenas, Ye Mao, Zexuan Zhao, San Chun Hin, Anirudhha Hazarika, Ke Xu, Luca Miglietta, Zara Breese, Alison H. Holmes, Karen Brengel-Pesce, Laurent Drazek, and Jesus Rodriguez-Manzano.</p><p dir="ltr">This repository contains the processed amplification curves (ACs) datasets and trained model checkpoints supporting the analyses reported in the manuscript above.</p><p dir="ltr">The accompanying analysis and model-training code is available at:</p><p dir="ltr">https://github.com/lkreitmann-bmx/ACA_BYOL_qPCR</p><p>---</p><p dir="ltr">Overview</p><p dir="ltr">The study investigates amplification curve analysis (ACA) as a strategy for increasing the multiplexing capacity of TaqMan real-time PCR (qPCR). It combines:</p><p dir="ltr">Stoichiometric feature encoding, in which forward primer, reverse primer, and probe concentrations are varied to generate target-specific AC morphologies.</p><p dir="ltr">Self-supervised representation learning using Bootstrap Your Own Latent (BYOL) on digital qPCR (dqPCR) amplification curves.</p><p dir="ltr">Conditional domain adversarial training using a transformer-based CDAN (T-CDAN) to improve transfer across experimental domains.</p><p dir="ltr">Co-amplification analysis to determine whether double- and triple-target amplification events remain distinguishable.</p><p dir="ltr">The deposit is intended to provide the datasets required to reproduce the main analyses and the trained neural-network checkpoints used in the manuscript. Additional raw instrument files are not included in this deposit and are available from the corresponding author upon reasonable request, subject to institutional and/or commercial data-sharing agreements.</p><p dir="ltr"><br></p> 2026-09-13T08:55:57Z Dataset Dataset 10.6084/m9.figshare.33685081.v1 https://figshare.com/articles/dataset/ACA_BYOL_qPCR_datasets_and_model_checkpoints/33685081 CC BY 4.0