Stefely, J. A. et al. Mitochondrial protein functions elucidated by multi-omic mass spectrometry profiling. Nat. Biotechnol. 34, 1191–1197 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Karczewski, K. J. & Snyder, M. P. Integrative omics for health and disease. Nat. Rev. Genet. 19, 299–310 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
Rhodes, D. R. & Chinnaiyan, A. M. Integrative analysis of the cancer transcriptome. Nat. Genet. 37, S31–S37 (2005).
Article
CAS
PubMed
Google Scholar
Chung, M. et al. Best practices on the differential expression analysis of multi-species RNA-seq. Genome Biol. 22, 121 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yamada, R. et al. Interpretation of omics data analyses. J. Hum. Genet. 66, 93–102 (2021).
Article
PubMed
Google Scholar
Subramanian, I. et al. Multi-omics data integration, interpretation, and its application. Bioinform. Biol. Insights 14, 1177932219899051 (2020).
Article
PubMed
PubMed Central
Google Scholar
Shu, T. et al. Plasma proteomics identify biomarkers and pathogenesis of COVID-19. Immunity 53, 1108–1122.e5 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Shui, K. et al. Small-sample learning reveals propionylation in determining global protein homeostasis. Nat. Commun. 14, 2813 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yuan, Y. et al. PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest. Nat. Commun. 13, 5237 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Hirschberg, J. & Manning, C. D. Advances in natural language processing. Science 349, 261–266 (2015).
Article
CAS
PubMed
Google Scholar
ChatGPT: Optimizing Language Models for Dialogue (OpenAI, 2022).
Christiano, P. F. et al. Deep reinforcement learning from human preferences. In Proc. 31st International Conference on Neural Information Processing Systems (eds von Luxburg, U. et al.) 4302–4310 (Curran, 2017).
Brown, T. B. et al. Language models are few-shot learners. In Proc. 34th Conference on Neural Information Processing Systems (eds Larochelle, H. et al.) 1–25 (2020).
Wei, J. S. et al. Chain-of-thought prompting elicits reasoning in large language models. In Proc. 36th International Conference on Neural Information Processing Systems (eds Koyejo, S. et al.) 24824–24837 (Curran, 2022).
Klionsky, D. J. et al. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition). Autophagy 17, 1–382 (2021).
Article
PubMed
PubMed Central
Google Scholar
Ulgherait, M. et al. Circadian autophagy drives iTRF-mediated longevity. Nature 598, 353–358 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Skrott, Z. et al. Alcohol-abuse drug disulfiram targets cancer via p97 segregase adaptor NPL4. Nature 552, 194–199 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhao, M.-M. et al. Novel cleavage sites identified in SARS-CoV-2 spike protein reveal mechanism for cathepsin L-facilitated viral infection and treatment strategies. Cancer Discov. 8, 53 (2022).
CAS
Google Scholar
Podgorski, J. & Berg, M. Global threat of arsenic in groundwater. Science 368, 845–850 (2020).
Article
CAS
PubMed
Google Scholar
Diamantopoulou, Z. et al. The metastatic spread of breast cancer accelerates during sleep. Nature 607, 156–162 (2022).
Article
CAS
PubMed
Google Scholar
Obradović, M. M. S. et al. Glucocorticoids promote breast cancer metastasis. Nature 567, 540–544 (2019).
Article
PubMed
Google Scholar
Hirota, T. & King, B. H. Autism spectrum disorder: a review. JAMA 329, 157–168 (2023).
Article
CAS
PubMed
Google Scholar
Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792.e21 (2022).
Article
CAS
PubMed
Google Scholar
Tang, F. et al. A pan-cancer single-cell panorama of human natural killer cells. Cell 186, 4235–4251.e20 (2023).
Article
CAS
PubMed
Google Scholar
Velmeshev, D. et al. Single-cell analysis of prenatal and postnatal human cortical development. Science 382, eadf0834 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Deng, W. et al. THANATOS: an integrative data resource of proteins and post-translational modifications in the regulation of autophagy. Autophagy 14, 296–310 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
Han, Z. et al. Model-based analysis uncovers mutations altering autophagy selectivity in human cancer. Nat. Commun. 12, 3258 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Santos, A. et al. A knowledge graph to interpret clinical proteomics data. Nat. Biotechnol. 40, 692–702 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang, Z. et al. Large graph models: a perspective. Preprint at https://doi.org/10.48550/arXiv.2308.14522 (2023).
Yu, H. et al. Annotation transfer between genomes: protein–protein interologs and protein–DNA regulogs. Genome Res. 14, 1107–1118 (2004).
Article
CAS
PubMed
PubMed Central
Google Scholar
Lyu, Y., Huang, X. & Zhang, Z. Revisiting 2D convolutional neural networks for graph-based applications. IEEE Trans. Pattern Anal. Mach. Intell. 45, 6909–6922 (2023).
Article
PubMed
Google Scholar
Díez, J., Walter, D., Muñoz-Pinedo, C. & Gabaldón, T. DeathBase: a database on structure, evolution and function of proteins involved in apoptosis and other forms of cell death. Cell Death Differ. 17, 735–736 (2010).
Article
PubMed
Google Scholar
Homma, K., Suzuki, K. & Sugawara, H. The Autophagy Database: an all-inclusive information resource on autophagy that provides nourishment for research. Nucleic Acids Res. 39, D986–D990 (2011).
Article
CAS
PubMed
Google Scholar
Moussay, E. et al. The acquisition of resistance to TNFα in breast cancer cells is associated with constitutive activation of autophagy as revealed by a transcriptome analysis using a custom microarray. Autophagy 7, 760–770 (2011).
Article
CAS
PubMed
Google Scholar
Xu, J. & Li, Y. H. miRDeathDB: a database bridging microRNAs and the programmed cell death. Cell Death Differ. 19, 1571 (2012).
Article
CAS
PubMed
PubMed Central
Google Scholar
Arntzen, M., Bull, V. H. & Thiede, B. Cell death proteomics database: consolidating proteomics data on cell death. J. Proteome Res. 12, 2206–2213 (2013).
Article
CAS
PubMed
Google Scholar
Wanichthanarak, K., Cvijovic, M., Molt, A. & Petranovic, D. yApoptosis: yeast apoptosis database. Database 2013, bat068 (2013).
Article
PubMed
PubMed Central
Google Scholar
Türei, D. et al. Autophagy Regulatory Network—a systems-level bioinformatics resource for studying the mechanism and regulation of autophagy. Autophagy 11, 155–165 (2015).
Article
PubMed
PubMed Central
Google Scholar
Wu, D. et al. ncRDeathDB: a comprehensive bioinformatics resource for deciphering network organization of the ncRNA-mediated cell death system. Autophagy 11, 1917–1926 (2015).
Article
CAS
PubMed
PubMed Central
Google Scholar
Wang, N. N. et al. HAMdb: a database of human autophagy modulators with specific pathway and disease information. J. Cheminform. 10, 34 (2018).
Article
CAS
PubMed
PubMed Central
Google Scholar
Chen, K. et al. Autophagy and Tumor Database: ATdb, a novel database connecting autophagy and tumor. Database https://doi.org/10.1093/database/baaa052 (2020).
Zhou, N. & Bao, J. FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis–disease associations. Database https://doi.org/10.1093/database/baaa021 (2020).
Zhang, L. et al. MCDB: a comprehensive curated mitotic catastrophe database for retrieval, protein sequence alignment, and target prediction. Acta Pharm. Sin. B 11, 3092–3104 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Sun, Y. J., Sheng, D. F., Zhou, Z. H. & Wu, Y. F. AI hallucination: towards a comprehensive classification of distorted information in artificial intelligence-generated content. Hum. Soc. Sci. Commun. https://doi.org/10.1057/S41599-024-03811-X (2024).
Bang, Y. et al. A multitask, multilingual, multimodal evaluation of ChatGPT on reasoning, hallucination, and interactivity. Preprint at https://arxiv.org/abs/2302.04023 (2023).
Zhu, W., Swaminathan, G. & Plowey, E. D. GA binding protein augments autophagy via transcriptional activation of BECN1-PIK3C3 complex genes. Autophagy 10, 1622–1636 (2014).
Article
CAS
PubMed
PubMed Central
Google Scholar
Sun, W., Jia, M., Feng, Y. & Cheng, X. Lactate is a bridge linking glycolysis and autophagy through lactylation. Autophagy 19, 3240–3241 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Fujioka, Y. et al. Structural basis of starvation-induced assembly of the autophagy initiation complex. Nat. Struct. Mol. Biol. 21, 513–521 (2014).
Article
CAS
PubMed
Google Scholar
Schreiber, A. et al. Multilayered regulation of autophagy by the Atg1 kinase orchestrates spatial and temporal control of autophagosome formation. Mol. Cell 81, 5066–5081.e10 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Feng, Y. et al. Phosphorylation of Atg9 regulates movement to the phagophore assembly site and the rate of autophagosome formation. Autophagy 12, 648–658 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Cowley, M. J. et al. PINA v2.0: mining interactome modules. Nucleic Acids Res. 40, D862–D865 (2012).
Article
CAS
PubMed
Google Scholar
Das, J. & Yu, H. HINT: high-quality protein interactomes and their applications in understanding human disease. BMC Syst. Biol. 6, 92 (2012).
Article
PubMed
PubMed Central
Google Scholar
Razick, S., Magklaras, G. & Donaldson, I. M. iRefIndex: a consolidated protein interaction database with provenance. BMC Bioinformatics 9, 405 (2008).
Article
PubMed
PubMed Central
Google Scholar
Oughtred, R. et al. The BioGRID interaction database: 2019 update. Nucleic Acids Res. 47, D529–D541 (2019).
Article
CAS
PubMed
Google Scholar
Calderone, A., Castagnoli, L. & Cesareni, G. mentha: a resource for browsing integrated protein-interaction networks. Nat. Methods 10, 690–691 (2013).
Article
CAS
PubMed
Google Scholar
Kotlyar, M., Pastrello, C., Malik, Z. & Jurisica, I. IID 2018 update: context-specific physical protein–protein interactions in human, model organisms and domesticated species. Nucleic Acids Res. 47, D581–D589 (2019).
Article
CAS
PubMed
Google Scholar
Li, T. et al. A scored human protein–protein interaction network to catalyze genomic interpretation. Nat. Methods 14, 61–64 (2017).
Article
CAS
PubMed
Google Scholar
Galluzzi, L. et al. Molecular definitions of autophagy and related processes. EMBO J. 36, 1811–1836 (2017).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yi, C. et al. Formation of a Snf1-Mec1-Atg1 module on mitochondria governs energy deprivation-induced autophagy by regulating mitochondrial respiration. Dev. Cell 41, 59–71.e54 (2017).
Article
CAS
PubMed
Google Scholar
Yi, C., Tong, J. J. & Yu, L. Mitochondria: the hub of energy deprivation-induced autophagy. Autophagy 14, 1084–1085 (2018).
CAS
PubMed
Google Scholar
Clement, S. T., Dixit, G. & Dohlman, H. G. Regulation of yeast G protein signaling by the kinases that activate the AMPK homolog Snf1. Sci. Signal. 6, ra78 (2013).
Article
PubMed
PubMed Central
Google Scholar
Mok, J. et al. Deciphering protein kinase specificity through large-scale analysis of yeast phosphorylation site motifs. Sci. Signal. 3, ra12 (2010).
Article
PubMed
PubMed Central
Google Scholar
Asano, S. et al. Direct phosphorylation and activation of a Nim1-related kinase Gin4 by Elm1 in budding yeast. J. Biol. Chem. 281, 27090–27098 (2006).
Article
CAS
PubMed
Google Scholar
Hu, Y. et al. The disulfiram/copper complex induces autophagic cell death in colorectal cancer by targeting ULK1. Front. Pharmacol. 12, 752825 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Jivan, R. et al. Disulfiram with or without metformin inhibits oesophageal squamous cell carcinoma in vivo. Cancer Lett. 417, 1–10 (2018).
Article
CAS
PubMed
Google Scholar
Wu, X. et al. Suppressing autophagy enhances disulfiram/copper-induced apoptosis in non-small cell lung cancer. Eur. J. Pharmacol. 827, 1–12 (2018).
Article
CAS
PubMed
Google Scholar
Xu, S. et al. Inhibition of cathepsin L alleviates the microglia-mediated neuroinflammatory responses through caspase-8 and NF-κB pathways. Neurobiol. Aging 62, 159–167 (2018).
Article
CAS
PubMed
Google Scholar
Liu, H. et al. Oxidized DJ-1 activates the p-IKK/NF-κB/Beclin1 pathway by binding PTEN to induce autophagy and exacerbate myocardial ischemia-reperfusion injury. Eur. J. Pharmacol. 971, 176496 (2024).
Article
CAS
PubMed
Google Scholar
Tate, J. G. et al. COSMIC: the Catalogue Of Somatic Mutations In Cancer. Nucleic Acids Res. 47, D941–D947 (2019).
Article
CAS
PubMed
Google Scholar
Kenig, S., Frangež, R., Pucer, A. & Lah, T. Inhibition of cathepsin L lowers the apoptotic threshold of glioblastoma cells by up-regulating p53 and transcription of caspases 3 and 7. Apoptosis 16, 671–682 (2011).
Article
CAS
PubMed
Google Scholar
Zhao, M. M. et al. Cathepsin L plays a key role in SARS-CoV-2 infection in humans and humanized mice and is a promising target for new drug development. Signal Transduct. Target. Ther. https://doi.org/10.1038/s41392-021-00558-8 (2021).
Sudhan, D. R., Pampo, C., Rice, L. & Siemann, D. W. Cathepsin L inactivation leads to multimodal inhibition of prostate cancer cell dissemination in a preclinical bone metastasis model. Int. J. Cancer 138, 2665–2677 (2016).
Article
CAS
PubMed
PubMed Central
Google Scholar
Richard, V. et al. The double agents in liquid biopsy: promoter and informant biomarkers of early metastases in breast cancer. Mol. Cancer 21, 95 (2022).
Article
CAS
PubMed
PubMed Central
Google Scholar
Xu, J. et al. ATP11B inhibits breast cancer metastasis in a mouse model by suppressing externalization of nonapoptotic phosphatidylserine. J. Clin. Invest. https://doi.org/10.1172/jci149473 (2022).
Jiang, C. C. et al. Signalling pathways in autism spectrum disorder: mechanisms and therapeutic implications. Signal Transduct. Target. Ther. 7, 229 (2022).
Article
PubMed
PubMed Central
Google Scholar
Bheda, A., Creek, K. E. & Pirisi, L. Loss of p53 induces epidermal growth factor receptor promoter activity in normal human keratinocytes. Oncogene 27, 4315–4323 (2008).
Article
CAS
PubMed
PubMed Central
Google Scholar
Linder, M. et al. EGFR is required for FOS-dependent bone tumor development via RSK2/CREB signaling. EMBO Mol. Med. https://doi.org/10.15252/emmm.201809408 (2018).
Rives, A. et al. Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. Proc. Natl Acad. Sci. USA 118, e2016239118 (2021).
Article
CAS
PubMed
PubMed Central
Google Scholar
Madani, A. et al. Large language models generate functional protein sequences across diverse families. Nat. Biotechnol. 41, 1099–1106 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Yang, F. et al. scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data. Nat. Mach. Intell. 4, 852 (2022).
Article
Google Scholar
Theodoris, C. V. et al. Transfer learning enables predictions in network biology. Nature 618, 616–624 (2023).
Article
CAS
PubMed
PubMed Central
Google Scholar
Cui, H. T. et al. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat. Methods 21, 1470–1480 (2024).
Article
CAS
PubMed
Google Scholar
Wu, A. et al. Causality for large language models. Preprint at https://arxiv.org/abs/2410.15319 (2024).
Lee, S. et al. Reasoning abilities of large language models: in-depth analysis on the abstraction and reasoning corpus. Preprint at https://arxiv.org/abs/2403.11793 (2024).
Kipf, T. N. & Welling, M. Variational graph auto-encoders. Preprint at https://arxiv.org/abs/1611.07308 (2016).
Wu, Z. H. et al. A comprehensive survey on graph neural networks. IEEE Trans. Neural Netw. Learn. Syst. 32, 4–24 (2021).
Article
PubMed
Google Scholar
Miao, Z., Humphreys, B. D., McMahon, A. P. & Kim, J. Multi-omics integration in the age of million single-cell data. Nat. Rev. Nephrol. 17, 710–724 (2021).
Article
PubMed
PubMed Central
Google Scholar
Ma, A. et al. Integrative methods and practical challenges for single-cell multi-omics. Trends Biotechnol. 38, 1007–1022 (2020).
Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang, Y. et al. DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae. Autophagy 16, 626–640 (2020).
Article
CAS
PubMed
Google Scholar
Tang, D., Zhang, C., Peng, D. & Xue, Y. Transcriptome of Saccharomyces cerevisiae during glucose starvation. Datasets. SRA https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA912308 (2025).
Tang, D., Zhang, C., Peng, D. & Xue, Y. The proteome and phosphoproteome of Saccharomyces cerevisiae during glucose starvation. Datasets. iProX https://www.iprox.cn//page/project.html?id=IPX0005607000 (2025).
Tang, D., Zhang, C., Peng, D. & Xue, Y. LyMOI: large hybrid models for omics interpretation. Source code. GitHub https://github.com/BioCUCKOO/LyMOI (2025).