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This paper introduces PROTEUS, a fully automated system that produces data-driven hypotheses from raw data files.
Han, X., Zhang, Z., Ding, N., Gu, Y., Liu, X., Huo, Y., Qiu, J., Yao, Y., Zhang, A., Zhang, L., et al
2021
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Zhou, J., Zhang, B., Chen, X., Li, H., Xu, X., Chen, S., He, W., Xu, C., Gao, X.: An AI Agent for Fully Automated Multi-omic Analyses (2023)
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2024
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Xiao, Y., Liu, J., Zheng, Y., Xie, X., Hao, J., Li, M., Wang, R., Ni, F., Li, Y., Luo, J., Jiao, S., Peng, J.: CellAgent: An LLM-driven multi-agent framework for automated single-cell data analysis. bioRxiv 2024.05.13.593861 (2024)
2024
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Liu, Y., Shen, R., Zhou, L., Xiao, Q., Yuan, J., Li, Y.: A data-intelligence-intensive bioinformatics copilot system for large-scale omics researches and scientific insights. bioRxiv 2024.05.19.594895 (2024)
2024
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Xin, Q., Kong, Q., Ji, H.: BioInformatics agent (BIA): Unleashing the power of large language models to reshape bioinformatics workflow. bioRxiv 2024.05.22.595240 (2024)
2024
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Lu, Y.-C., Varghese, A., Nahar, R., Chen, H., Shao, K., Bao, X., Li, C.: scChat: A Large Language Model-Powered Co-Pilot for Contextualized Single-Cell RNA Sequencing Analysis (2024). https://doi.org/10.1101/2024.10.01.616063
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Boiko, D.A., MacKnight, R., Kline, B., Gomes, G.: Autonomous chemical research with large language models 624
2024
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Davidson-Pilon, C.: Lifelines, Survival Analysis in Python. https://doi.org/10.5281/zenodo.12549337 . https://zenodo.org/records/12549337 Accessed 2024-09-15
2024
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Rajczewski, A.T., Jagtap, P.D., Griffin, T.J.: An overview of technologies for MS-based proteomics-centric multi-omics 19
2025
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Chen, C., Wang, J., Pan, D., Wang, X., Xu, Y., Yan, J., Wang, L., Yang, X., Yang, M., Liu, G.-P.: Applications of multi-omics analysis in human diseases 4
2025
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Krassowski, M., Das, V., Sahu, S.K., Misra, B.B.: State of the field in multi-omics research: From computational needs to data mining and sharing 11
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Cui, M., Cheng, C., Zhang, L.: High-throughput proteomics: a methodological mini-review 102
2025
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Messner, C.B., Demichev, V., Wang, Z., Hartl, J., Kustatscher, G., Mülleder, M., Ralser, M.: Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology 23
2025
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Yanai, I., Lercher, M.: A hypothesis is a liability 21
2025
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2025
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Liu, Q., Zhang, J., Guo, C., Wang, M., Wang, C., Yan, Y., Sun, L., Wang, D., Zhang, L., Yu, H., Hou, L., Wu, C., Zhu, Y., Jiang, G., Zhu, H., Zhou, Y., Fang, S., Zhang, T., Hu, L., Li, J., Liu, Y., Zhang, H., Zhang, B., Ding, L., Robles, A.I., Rodriguez, H., Gao, D., Ji, H., Zhou, H., Zhang, P.: Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies 187
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Mazzocchi, F.: Could big data be the end of theory in science? https://doi.org/10.15252/embr.201541001 . Accessed 2025-05-01
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Wang, H., He, Y., Coelho, P.P., Bucci, M., Nazir, A., Chen, B., Trinh, L., Zhang, S., Huang, K., Chandrasekar, V., Chung, D.C., Hao, M., Leote, A.C., Lee, Y., Li, B., Liu, T., Liu, J., Lopez, R., Lucas, T., Ma, M., Makarov, N., McGinnis, L., Peng, L., Ra, S., Scalia, G., Singh, A., Tao, L., Uehara, M., Wang, C., Wei, R., Copping, R., Rozenblatt-Rosen, O., Leskovec, J., Regev, A.: SpatialAgent: An autonomous AI agent for spatial biology. bioRxiv. Pages: 2025.04.03.646459 Section: New Results. https://doi.org/10.1101/2025.04.03.646459 . https://www.biorxiv.org/content/10.1101/2025.04.03.646459v1 Accessed 2025-05-02
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