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Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma

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Published in:Discover Oncology
Format: Online Article RSS Article
Published: 2026
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container_title Discover Oncology
description
discipline_display Endocrinology
discipline_facet Endocrinology
format Online Article
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genre Journal Article
id rss_article:104518
institution FRELIP
journal_source_facet Discover Oncology
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publishDate 2026
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spellingShingle Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
Endocrinology
General
Endocrinology
sub_discipline_display General
sub_discipline_facet General
subject_display Endocrinology
General
Endocrinology
subject_facet Endocrinology
General
Endocrinology
title Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_alt Integración de toxicología de redes, aprendizaje automático y secuenciación de células individuales identifica vínculos moleculares candidatos entre contaminantes del aire y carcinoma hepatocelular
Intégration de la toxicologie réseau, de l'apprentissage automatique et du séquençage unicellulaire pour identifier les liens moléculaires candidats entre les polluants atmosphériques et le carcinome hépatocellulaire
Integração de toxicologia de rede, aprendizado de máquina e sequenciamento de célula única identifica ligações moleculares candidatas entre poluentes atmosféricos e carcinoma hepatocelular
title_auth Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_es_txt Integración de toxicología de redes, aprendizaje automático y secuenciación de células individuales identifica vínculos moleculares candidatos entre contaminantes del aire y carcinoma hepatocelular
title_fr_txt Intégration de la toxicologie réseau, de l'apprentissage automatique et du séquençage unicellulaire pour identifier les liens moléculaires candidats entre les polluants atmosphériques et le carcinome hépatocellulaire
title_full Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_fullStr Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_full_unstemmed Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_pt_txt Integração de toxicologia de rede, aprendizado de máquina e sequenciamento de célula única identifica ligações moleculares candidatas entre poluentes atmosféricos e carcinoma hepatocelular
title_short Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
title_sort integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma
topic Endocrinology
General
Endocrinology
url https://link.springer.com/article/10.1007/s12672-026-05569-x