Citation: | Ying Hou, Hongren Yao, Jin-Ming Lin. Recent advancements in single-cell metabolic analysis for pharmacological research[J]. Journal of Pharmaceutical Analysis, 2023, 13(10): 1102-1116. doi: 10.1016/j.jpha.2023.08.014 |
R. Zenobi, Single-cell metabolomics: Analytical and biological perspectives, Science 342 (2013), 1243259.
|
S.J. Altschuler, L.F. Wu, Cellular heterogeneity: Do differences make a difference? Cell 141 (2010) 559-563.
|
Y. Oren, M. Tsabar, M.S. Cuoco, et al., Cycling cancer persister cells arise from lineages with distinct programs, Nature 596 (2021) 576-582.
|
A.M. Wheeler, C.D. Eberhard, E.P. Mosher, et al., Achieving a deeper understanding of drug metabolism and responses using single-cell technologies, Drug Metab. Dispos. 51 (2023) 350-359.
|
Y. Zhang, S. Chen, F. Fan, et al., Neurotoxicity mechanism of aconitine in HT22 cells studied by microfluidic chip-mass spectrometry, J. Pharm. Anal. 13 (2023) 88-98.
|
S. Ma, J. Wu, Z. Liu, et al., Quantitative characterization of cell physiological state based on dynamical cell mechanics for drug efficacy indication, J. Pharm. Anal. 13 (2023) 388-402.
|
T. Chen, C. Huang, Y. Wang, et al., Microfluidic methods for cell separation and subsequent analysis, Chin. Chem. Lett. 33 (2022) 1180-1192.
|
X. Lin, J. Su, S. Zhou, Microfluidic chip of concentration gradient and fluid shear stress on a single cell level, Chin. Chem. Lett. 33 (2022) 3133-3138.
|
Y. Jiao, L. Gao, Y. Ji, et al., Recent advances in microfluidic single-cell analysis and its applications in drug development, Trac Trends Anal. Chem. 157 (2022), 116796.
|
Y. Ai, F. Zhang, C. Wang, et al., Recent progress in lab-on-a-chip for pharmaceutical analysis and pharmacological/toxicological test, Trac Trends Anal. Chem. 117 (2019) 215-230.
|
Q. Zhong, X. Huang, R. Zhang, et al., Optical sensing strategies for probing single-cell secretion, ACS Sens. 7 (2022) 1779-1790.
|
G.Q. Wallace, J.F. Masson, From single cells to complex tissues in applications of surface-enhanced Raman scattering, Analyst 145 (2020) 7162-7185.
|
Q. Yang, X. Huang, B. Gao, et al., Advances in electrochemiluminescence for single-cell analysis, Analyst 148 (2023) 9-25.
|
Y. Lei, R. Tang, J. Xu, et al., Applications of single-cell sequencing in cancer research: Progress and perspectives, J. Hematol. Oncol. 14 (2021), 91.
|
M. Tajik, M. Baharfar, W.A. Donald, Single-cell mass spectrometry, Trends Biotechnol. 40 (2022) 1374-1392.
|
Z. Wu, P.J. Lawrence, A. Ma, et al., Single-cell techniques and deep learning in predicting drug response, Trends Pharmacol. Sci. 41 (2020) 1050-1065.
|
N. Shembekar, C. Chaipan, R. Utharala, et al., Droplet-based microfluidics in drug discovery, transcriptomics and high-throughput molecular genetics, Lab Chip 16 (2016) 1314-1331.
|
Y. Hou, S. Chen, Y. Zheng, et al., Droplet-based digital PCR (ddPCR) and its applications, Trac Trends Anal. Chem. 158 (2023), 116897.
|
D. Xu, W. Zhang, H. Li, et al., Advances in droplet digital polymerase chain reaction on microfluidic chips, Lab Chip 23 (2023) 1258-1278.
|
X. Yue, X. Fang, T. Sun, et al., Breaking through the Poisson Distribution: A compact high-efficiency droplet microfluidic system for single-bead encapsulation and digital immunoassay detection, Biosens. Bioelectron. 211 (2022), 114384.
|
J. Zhong, M. Liang, Q. Tang, et al., Selectable encapsulated cell quantity in droplets via label-free electrical screening and impedance-activated sorting, Mater. Today Bio. 19 (2023), 100594.
|
W. Zhang, N. Li, L. Lin, et al., Concentrating single cells in picoliter droplets for phospholipid profiling on a microfluidic system, Small 16 (2020), 1903402.
|
W. Zhang, N. Li, L. Lin, et al., Metabolism-based capture and analysis of circulating tumor cells in an open space, Anal. Chem. 93 (2021) 6955-6960.
|
W. Wu, S. Zhang, T. Zhang, et al., Immobilized droplet arrays in thermosetting oil for dynamic proteolytic assays of single cells, ACS Appl. Mater. Interfaces 13 (2021) 6081-6090.
|
T. Xie, Q. Zhang, W. Zhang, et al., Inkjet-patterned microdroplets as individual microenvironments for adherent single cell culture, Small 18 (2022), 2270097.
|
S.W. Wong, S. Lenzini, R. Bargi, et al., Controlled deposition of 3D matrices to direct single cell functions, Adv. Sci. 7 (2020), 2001066.
|
B. Ha, T.J. Kim, E. Moon, et al., Flow radiocytometry using droplet optofluidics, Biosens. Bioelectron. 194 (2021), 113565.
|
Y. Zhou, Z. Yu, M. Wu, et al., Single-cell sorting using integrated pneumatic valve droplet microfluidic chip, Talanta 253 (2023), 124044.
|
S.N. Agnihotri, G.S. Ugolini, M.R. Sullivan, et al., Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: Application in immunotherapies for cancer, Lab Chip 22 (2022) 3258-3267.
|
T. Khajvand, P. Huang, L. Li, et al., Interfacing droplet microfluidics with antibody barcodes for multiplexed single-cell protein secretion profiling, Lab Chip 21 (2021) 4823-4830.
|
P. Radfar, L. Ding, L.R. de la Fuente, et al., Rapid metabolomic screening of cancer cells via high-throughput static droplet microfluidics, Biosens. Bioelectron. 223 (2023), 114966.
|
R. Xie, Y. Liu, S. Wang, et al., Combinatorial perturbation sequencing on single cells using microwell-based droplet random pairing, Biosens. Bioelectron. 220 (2023), 114913.
|
M. Zhang, Y. Zou, X. Xu, et al., Highly parallel and efficient single cell mRNA sequencing with paired picoliter chambers, Nat. Commun. 11 (2020), 2118.
|
S. Lin, K. Yin, Y. Zhang, et al., Well-TEMP-seq as a microwell-based strategy for massively parallel profiling of single-cell temporal RNA dynamics, Nat. Commun. 14 (2023), 1272.
|
Q. Zhang, S. Feng, L. Lin, et al., Emerging open microfluidics for cell manipulation, Chem. Soc. Rev. 50 (2021) 5333-5348.
|
S. Mao, W. Zhang, Q. Huang, et al., In situ scatheless cell detachment reveals correlation between adhesion strength and viability at single-cell resolution, Angew. Chem. Int. Ed. 57 (2018) 236-240.
|
S. Mao, Q. Zhang, H. Li, et al., Measurement of cell-matrix adhesion at single-cell resolution for revealing the functions of biomaterials for adherent cell culture, Anal. Chem. 90 (2018) 9637-9643.
|
S. Mao, Q. Zhang, H. Li, et al., Adhesion analysis of single circulating tumor cells on a base layer of endothelial cells using open microfluidics, Chem. Sci. 9 (2018) 7694-7699.
|
Q. Zhang, S. Mao, W. Li, et al., Microfluidic adhesion analysis of single glioma cells for evaluating the effect of drugs, Sci. China Chem. 63 (2020) 865-870.
|
Q. Zhang, S. Mao, M. Khan, et al., In situ partial treatment of single cells by laminar flow in the “open space”, Anal. Chem. 91 (2019) 1644-1650.
|
Q. Zhang, S. Feng, W. Li, et al., In situ stable generation of reactive intermediates by open microfluidic probe for subcellular free radical attack and membrane labeling, Angew. Chem. Int. Ed. 60 (2021) 8483-8487.
|
Q. Huang, S. Mao, M. Khan, et al., Single-cell identification by microfluidic-based in situ extracting and online mass spectrometric analysis of phospholipids expression, Chem. Sci. 11 (2020) 253-256.
|
X. Yi, Q. Zhang, T. Xie, et al., Microfluidic mixer for in situ ammonia analysis of single cells in mass spectrometry, Anal. Chem. 95 (2023) 2321-2328.
|
J. Lamanna, E.Y. Scott, H.S. Edwards, et al., Digital microfluidic isolation of single cells for-Omics, Nat. Commun. 11 (2020), 5632.
|
Q. Zhang, X. Xu, L. Lin, et al., Cilo-seq: Highly sensitive cell-in-library-out single-cell transcriptome sequencing with digital microfluidics, Lab Chip 22 (2022) 1971-1979.
|
X. Xu, L. Lin, J. Yang, et al., Simultaneous single-cell genome and transcriptome sequencing in nanoliter droplet with digital microfluidics identifying essential driving genes, Nano Today 46 (2022), 101596.
|
W. Li, M. Khan, L. Lin, et al., Monitoring H2O2 on the surface of single cells with liquid crystal elastomer microspheres, Angew. Chem. Int. Ed. 59 (2020) 9282-9287.
|
C. Wang, C. Wang, Y. Wu, et al., High-throughput, living single-cell, multiple secreted biomarker profiling using microfluidic chip and machine learning for tumor cell classification, Adv. Healthcare Mater. 11 (2022), 2102800.
|
Q.A. Alshammari, R. Pala, N. Katzir, et al., Label-free spectral imaging to study drug distribution and metabolism in single living cells, Sci. Rep. 11 (2021), 2703.
|
H. Kondo, C.D.H. Ratcliffe, S. Hooper, et al., Single-cell resolved imaging reveals intra-tumor heterogeneity in glycolysis, transitions between metabolic states, and their regulatory mechanisms, Cell Rep. 34 (2021), 108750.
|
C.A. Dawson, S.N. Mueller, G.J. Lindeman, et al., Intravital microscopy of dynamic single-cell behavior in mouse mammary tissue, Nat. Protoc. 16 (2021) 1907-1935.
|
A. R. Heaton, P. R. Rehani, A. Hoefges, et al., Single cell metabolic imaging of tumor and immune cells in vivo in melanoma bearing mice, Front. Oncol. 13 (2023), 1110503.
|
L. Pedro, P.J. Rudewicz, Analysis of live single cells by confocal microscopy and high-resolution mass spectrometry to study drug uptake, metabolism, and drug-induced phospholipidosis, Anal. Chem. 92 (2020) 16005-16015.
|
N. Altemose, A. Maslan, C. Rios-Martinez, et al., μDamID: A microfluidic approach for joint imaging and sequencing of protein-DNA interactions in single cells, Cell Syst. 11 (2020) 354-366.e9.
|
A. Gerard, A. Woolfe, G. Mottet, et al., High-throughput single-cell activity-based screening and sequencing of antibodies using droplet microfluidics, Nat. Biotechnol. 38 (2020) 715-721.
|
Y. Wen, J. Liu, H. He, et al., Single-cell analysis of signaling proteins provides insights into proapoptotic properties of anticancer drugs, Anal. Chem. 92 (2020) 12498-12508.
|
J. Liu, H. He, D. Xie, et al., Probing low-copy-number proteins in single living cells using single-cell plasmonic immunosandwich assays, Nat. Protoc. 16 (2021) 3522-3546.
|
J. Wang, K. Lin, H. Hu, et al., In vitro anticancer drug sensitivity sensing through single-cell Raman spectroscopy, Biosensors 11 (2021), 286.
|
Z. Zhao, C. Chen, H. Xiong, et al., Metabolic activity phenotyping of single cells with multiplexed vibrational probes, Anal. Chem. 92 (2020) 9603-9612.
|
C. Chen, Z. Zhao, N. Qian, et al., Multiplexed live-cell profiling with Raman probes, Nat. Commun. 12 (2021), 3405.
|
M. Li, Y. Nawa, S. Ishida, et al., Label-free chemical imaging of cytochrome P450 activity by Raman microscopy, Commun. Biol. 5 (2022), 778.
|
C.C. Hsu, J. Xu, B. Brinkhof, et al., A single-cell Raman-based platform to identify developmental stages of human pluripotent stem cell-derived neurons, Proc. Natl. Acad. Sci. U. S. A. 117 (2020) 18412-18423.
|
X. Wang, L. Ren, Z. Diao, et al., Robust spontaneous Raman flow cytometry for single-cell metabolic phenome profiling via pDEP-DLD-RFC, Adv. Sci. 10 (2023), 2370102.
|
H. Wang, Y. Ruan, L. Zhu, et al., An integrated electrochemical nanodevice for intracellular RNA collection and detection in single living cell, Angew. Chem. Int. Ed. 60 (2021) 13244-13250.
|
Y. Xu, Y. Ruan, H. Wang, et al., A practical electrochemical nanotool for facile quantification of amino acids in single cell, Small 17 (2021), 2100503.
|
A.N. Vaneev, P.V. Gorelkin, A.S. Garanina, et al., In vitro and in vivo electrochemical measurement of reactive oxygen species after treatment with anticancer drugs, Anal. Chem. 92 (2020) 8010-8014.
|
L. Zhou, N. Kasai, H. Nakajima, et al., In situ single-cell stimulation and real-time electrochemical detection of lactate response using a microfluidic probe, Anal. Chem. 93 (2021) 8680-8686.
|
E.Z. Macosko, A. Basu, R. Satija, et al., Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets, Cell 161 (2015) 1202-1214.
|
L. Tian, J.S. Jabbari, R. Thijssen, et al., Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing, Genome Biol. 22 (2021), 310.
|
F. Salmen, J. De Jonghe, T.S. Kaminski, et al., High-throughput total RNA sequencing in single cells using VASA-seq, Nat. Biotechnol. 40 (2022) 1780-1793.
|
Q. Qiu, P. Hu, X. Qiu, et al., Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq, Nat. Meth. 17 (2020) 991-1001.
|
W. Chen, O. Guillaume-Gentil, P.Y. Rainer, et al., Live-seq enables temporal transcriptomic recording of single cells, Nature 608 (2022) 733-740.
|
M. Meyer, A. Paquet, M.J. Arguel, et al., Profiling the non-genetic origins of cancer drug resistance with a single-cell functional genomics approach using predictive cell dynamics, Cell Syst. 11 (2020) 367-374.e5.
|
Q. Tang, L. Liu, Y. Guo, et al., Optical cell tagging for spatially resolved single-cell RNA sequencing, Angew. Chem. 134 (2022), e202113929.
|
M.R. Vahid, E.L. Brown, C.B. Steen, et al., High-resolution alignment of single-cell and spatial transcriptomes with CytoSPACE, Nat. Biotechnol. (2023). https://doi.org/10.1038/s41587-41023-01697-41589.
|
X. Pan, H. Yao, S. Zhang, et al., Recent progress in mass spectrometry for single-cell metabolomics, Curr. Opin. Chem. Biol. 71 (2022), 102226.
|
X. Men, C. Wu, X. Zhang, et al., Tracking cellular transformation of As(III) in HepG2 cells by single-cell focusing/capillary electrophoresis coupled to ICP-MS, Anal. Chim. Acta 1226 (2022), 340268.
|
S.Y. Lim, Z.E. Low, R.P.W. Tan, et al., Single-cell and bulk ICP-MS investigation of accumulation patterns of Pt-based metallodrugs in cisplatin-sensitive and-resistant cell models, Metallomics. 14 (2022), mfac085.
|
Y. Meng, X. Cheng, T. Wang, et al., Micro-lensed fiber laser desorption mass spectrometry imaging reveals subcellular distribution of drugs within single cells, Angew. Chem. Int. Ed. 59 (2020) 17864-17871.
|
X. Cheng, Z. Yin, L. Rong, et al., Subcellular chemical imaging of structurally similar acridine drugs by near-field laser desorption/laser postionization mass spectrometry, Nano Res. 13 (2020) 745-751.
|
F. Jia, J. Wang, Y. Zhao, et al., In situ visualization of proteins in single cells by time-of-flight-secondary ion mass spectrometry coupled with genetically encoded chemical tags, Anal. Chem. 92 (2020) 15517-15525.
|
A. Vegvari, J.E. Rodriguez, R.A. Zubarev, Single-cell chemical proteomics (SCCP) interrogates the timing and heterogeneity of cancer cell commitment to death, Anal. Chem. 94 (2022) 9261-9269.
|
A.D. Brunner, M. Thielert, C. Vasilopoulou, et al., Ultra-high sensitivity mass spectrometry quantifies single-cell proteome changes upon perturbation, Mol. Syst. Biol. 18 (2022), e10798.
|
G. Zhu, W. Zhang, Y. Zhao, et al., Single-cell metabolomics-based strategy for studying the mechanisms of drug action, Anal. Chem. 95 (2023) 4712-4720.
|
E. Hiyama, A. Ali, S. Amer, et al., Direct lipido-metabolomics of single floating cells for analysis of circulating tumor cells by live single-cell mass spectrometry, Anal. Sci. 31 (2015) 1215-1217.
|
A. Ali, Y. Abouleila, S. Amer, et al., Quantitative live single-cell mass spectrometry with spatial evaluation by three-dimensional holographic and tomographic laser microscopy, Anal. Sci. 32 (2016) 125-127.
|
E. Cuypers, B.S.R. Claes, R. Biemans, et al., ‘on the spot’ digital pathology of breast cancer based on single-cell mass spectrometry imaging, Anal. Chem. 94 (2022) 6180-6190.
|
S. Xu, M. Liu, Y. Bai, et al., Multi-dimensional organic mass cytometry: Simultaneous analysis of proteins and metabolites on single cells, Angew. Chem. Int. Ed. 60 (2021) 1806-1812.
|
H. Takeshima, Y. Yoda, M. Wakabayashi, et al., Low-dose DNA demethylating therapy induces reprogramming of diverse cancer-related pathways at the single-cell level, Clin. Epigenet. 12 (2020) 142.
|
S.R. Park, S. Namkoong, L. Friesen, et al., Single-cell transcriptome analysis of colon cancer cell response to 5-fluorouracil-induced DNA damage, Cell Rep. 32 (2020), 108077.
|
N. Onoda, A. Kawabata, K. Hasegawa, et al., Spatial and single-cell transcriptome analysis reveals changes in gene expression in response to drug perturbation in rat kidney, DNA Res. 29 (2022), dsac007.
|
J. Jones-Tabah, R.D. Martin, J.C. Tanny, et al., High-content single-cell Forster resonance energy transfer imaging of cultured striatal neurons reveals novel cross-talk in the regulation of nuclear signaling by protein kinase A and extracellular signal-regulated kinase 1/2, Mol. Pharmacol. 100 (2021) 526-539.
|
H. Li, Y. Gao, L. Xie, et al., Prednisone reprograms the transcriptional immune cell landscape in CNS autoimmune disease, Front. Immunol. 12 (2021), 739605.
|
M.C. Meinsohn, H.D. Saatcioglu, L. Wei, et al., Single-cell sequencing reveals suppressive transcriptional programs regulated by MIS/AMH in neonatal ovaries, Proc. Natl. Acad. Sci. U. S. A. 118 (2021), e2100920118.
|
A. Farkkila, D.C. Gulhan, J. Casado, et al., Author Correction: Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer, Nat. Commun. 11 (2020), 2543.
|
R. Zhong, Y. Zhang, D. Chen, et al., Single-cell RNA sequencing reveals cellular and molecular immune profile in a Pembrolizumab-responsive PD-L1-negative lung cancer patient, Cancer Immunol. Immunother. 70 (2021) 2261-2274.
|
N. Sahu, F.C. Grandi, N. Bhutani, A single-cell mass cytometry platform to map the effects of preclinical drugs on cartilage homeostasis, JCI Insight 7 (2022), e160702.
|
Y. Kashima, D. Shibahara, A. Suzuki, et al., Single-cell analyses reveal diverse mechanisms of resistance to EGFR tyrosine kinase inhibitors in lung cancer, Cancer Res. 81 (2021) 4835-4848.
|
S. Taavitsainen, N. Engedal, S. Cao, et al., Single-cell ATAC and RNA sequencing reveal pre-existing and persistent cells associated with prostate cancer relapse, Nat. Commun. 12 (2021), 5307.
|
Y.C. Cohen, M. Zada, S. Wang, et al., Identification of resistance pathways and therapeutic targets in relapsed multiple myeloma patients through single-cell sequencing, Nat. Med. 27 (2021) 491-503.
|
J. Goveia, K. Rohlenova, F. Taverna, et al., An integrated gene expression landscape profiling approach to identify lung tumor endothelial cell heterogeneity and angiogenic candidates, Cancer Cell 37 (2020) 21-36.e13.
|
J. Wu, Y. Xiao, J. Sun, et al., A single-cell survey of cellular hierarchy in acute myeloid leukemia, J. Hematol. Oncol. 13 (2020), 128.
|
H. Zhao, Y. Gao, J. Miao, et al., Single-cell RNA-seq highlights a specific carcinoembryonic cluster in ovarian cancer, Cell Death Dis. 12 (2021), 1082.
|
J. A. Taverna, C. N. Hung, D. T. Dearmond, et al., Single-cell proteomic profiling identifies combined AXL and JAK1 inhibition as a novel therapeutic strategy for lung cancer, Cancer Res. 80 (2020) 1551-1563.
|
D.H. Aggen, C.R. Ager, A.Z. Obradovic, et al., Blocking IL1 beta promotes tumor regression and remodeling of the myeloid compartment in a renal cell carcinoma model: Multidimensional analyses, Clin. Cancer Res. 27 (2021) 608-621.
|
J.Y. Sung, J.H. Cheong, Single cell analysis reveals reciprocal tumor-macrophage intercellular communications related with metabolic reprogramming in stem-like gastric cancer, Cells 11 (2022), 2373.
|
T. Selvin, E. Fasterius, M. Jarvius, et al., Single-cell transcriptional pharmacodynamics of trifluridine in a tumor-immune model, Sci. Rep. 12 (2022), 11960.
|
P.J. Lee, C.C. Ho, H. Ho, et al., Tumor microenvironment-based screening repurposes drugs targeting cancer stem cells and cancer-associated fibroblasts, Theranostics 11 (2021) 9667-9686.
|
C.J. Messner, L. Babrak, G. Titolo, et al., Single cell gene expression analysis in a 3D microtissue liver model reveals cell type-specific responses to pro-fibrotic TGF-β1 stimulation, Int. J. Mol. Sci. 22 (2021), 4372.
|
L.M. Smits, S. Magni, K. Kinugawa, et al., Single-cell transcriptomics reveals multiple neuronal cell types in human midbrain-specific organoids, Cell Tissue Res. 382 (2020) 463-476.
|
Y. Zhao, Z. Li, Y. Zhu, et al., Single-cell transcriptome analysis uncovers intratumoral heterogeneity and underlying mechanisms for drug resistance in hepatobiliary tumor organoids, Adv. Sci. 8 (2021), 2003897.
|
G. Inak, A. Rybak-Wolf, P. Lisowski, et al., Defective metabolic programming impairs early neuronal morphogenesis in neural cultures and an organoid model of Leigh syndrome, Nat. Commun. 12 (2021), 1929.
|
Z. Yuan, X. Fan, J.J. Zhu, et al., Presence of complete murine viral genome sequences in patient-derived xenografts, Nat. Commun. 12 (2021), 2031.
|
A. Ediriwickrema, A. Aleshin, J.G. Reiter, et al., Single-cell mutational profiling enhances the clinical evaluation of AML MRD, Blood Adv. 4 (2020) 943-952.
|
O. Rozenblatt-Rosen, A. Regev, P. Oberdoerffer, et al., The human tumor atlas network: Charting tumor transitions across space and time at single-cell resolution, Cell 181 (2020) 236-249.
|
M. Li, X. Zhang, K.S. Ang, et al., DISCO: A database of Deeply Integrated human Single-Cell Omics data, Nucleic Acids Res. 50 (2022) D596-D602.
|
B. Van de Sande, J.S. Lee, E. Mutasa-Gottgens, et al., Applications of single-cell RNA sequencing in drug discovery and development, Nat. Rev. Drug Discov. 22 (2023) 496-520.
|
Y. Cao, B. Su, X. Guo, et al., Potent neutralizing antibodies against SARS-CoV-2 identified by high-throughput single-cell sequencing of convalescent patients’ B cells, Cell 182 (2020) 73-84.e16.
|
R. Qi, Q. Zou, Trends and potential of machine learning and deep learning in drug study at single-cell level, Research 6 (2023), 005.
|