Advances in technology and the Internet have brought about the era of big data, and massive amounts of data have swept through almost every industry, especially in the medical field. With the penetration and expansion of information, countries around the world have started to build databases to explore the mysteries of health. In addition, the application of data storage, mining and analysis technologies in medicine has led to the involvement of biological big data in the study of many diseases. Long-term practice has revealed that combining biomacro data to analyze diseases can lead to more beneficial prevention and treatment options than conventional methods, which is a more favorable choice than ordinary methods. This review will present the progress of extensive data in medical research from the perspective of biological big data and neurodegenerative diseases (NDD), tumor, diabetes, and other applications, as well as the challenges and future directions of big data in medicine.

Zhanqing Luo. Advances in the Application of Biological Big Data in Medicine. Academic Journal of Medicine & Health Sciences (2022) Vol. 3, Issue 2: 22-32. https://doi.org/10.25236/AJMHS.2022.030204.

[1] Terzo, O., Ruiu, P., Bucci, E. & Xhafa, F. Data as a Service (DaaS) for sharing and processing of large data collections in the cloud. in Proceedings - 2013 7th International Conference on Complex, Intelligent, and Software Intensive Systems, CISIS 2013 475–480 (2013). doi:10.1109/CISIS.2013.87

[2] Meng, Zhenyu et al. "Weighted persistent homology for biomolecular data analysis." Scientific reports vol. 10,1 2079. 7 Feb. 2020, doi:10.1038/s41598-019-55660-3

[3] Liu, Tingting et al. "Applying high-performance computing in drug discovery and molecular simulation." National science review vol. 3,1 (2016): 49-63. doi:10.1093/nsr/nww003

[4] Ristevski, Blagoj, and Ming Chen. "Big Data Analytics in Medicine and Healthcare." Journal of integrative bioinformatics vol. 15,3 20170030. 10 May. 2018, doi:10.1515/jib-2017-0030

[5] Wang, Neng et al. "Direct inhibition of ACTN4 by ellagic acid limits breast cancer metastasis via regulation of β-catenin stabilization in cancer stem cells." Journal of experimental & clinical cancer research : CR vol. 36,1 172. 2 Dec. 2017, doi:10.1186/s13046-017-0635-9

[6] Nurk, Sergey et al. "The complete sequence of a human genome." Science (New York, N.Y.) vol. 376,6588 (2022): 44-53. doi:10.1126/science.abj6987

[7] Gammon, Katharine. "Neurodegenerative disease: brain windfall." Nature vol. 515,7526 (2014): 299-300. doi:10.1038/nj7526-299a

[8] Ross, Christopher A, and Michelle A Poirier. "Protein aggregation and neurodegenerative disease." Nature medicine vol. 10 Suppl (2004): S10-7. doi:10.1038/nm1066

[9] Lingor, Paul et al. "Axonal degeneration as a therapeutic target in the CNS." Cell and tissue research vol. 349,1 (2012): 289-311. doi:10.1007/s00441-012-1362-3

[10] Longhena, Francesca et al. "Targeting of Disordered Proteins by Small Molecules in Neurodegenerative Diseases." Handbook of experimental pharmacology vol. 245 (2018): 85-110. doi:10.1007/164_2017_60

[11] Donev, Rossen et al. "Neuronal death in Alzheimer's disease and therapeutic opportunities." Journal of cellular and molecular medicine vol. 13,11-12 (2009): 4329-48. doi:10.1111/ j.1582-4934.2009.00889.x

[12] Yao, Zhi, and Nicholas W Wood. "Cell death pathways in Parkinson's disease: role of mitochondria." Antioxidants & redox signaling vol. 11,9 (2009): 2135-49. doi:10.1089/ars.2009.2624

[13] Fischer, Lindsey R et al. "Amyotrophic lateral sclerosis is a distal axonopathy: evidence in mice and man." Experimental neurology vol. 185,2 (2004): 232-40. doi:10.1016/j.expneurol.2003.10.004

[14] Ballatore, Carlo et al. "Tau-mediated neurodegeneration in Alzheimer's disease and related disorders." Nature reviews. Neuroscience vol. 8,9 (2007): 663-72. doi:10.1038/nrn2194

[15] Signaevsky, Maxim et al. "Artificial intelligence in neuropathology: deep learning-based assessment of tauopathy." Laboratory investigation; a journal of technical methods and pathology vol. 99,7 (2019): 1019-1029. doi:10.1038/s41374-019-0202-4

[16] Saberi-Bosari, Sahand et al. "Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock." BMC biology vol. 18,1 130. 23 Sep. 2020, doi: 10.1186/s12915-020-00861-w

[17] Thompson, Paul M et al. "The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data." Brain imaging and behavior vol. 8,2 (2014): 153-82. doi:10.1007 /s11682-013-9269-5

[18] Ashbrook, David G et al. "Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease." BMC genomics vol. 15,1 850. 3 Oct. 2014, doi:10.1186/1471-2164-15-850

[19] Cizeron, Mélissa et al. "A brainwide atlas of synapses across the mouse life span." Science (New York, N.Y.) vol. 369,6501 (2020): 270-275. doi:10.1126/science.aba3163

[20] Jia, Longfei et al. "Prevalence, risk factors, and management of dementia and mild cognitive impairment in adults aged 60 years or older in China: a cross-sectional study." The Lancet. Public health vol. 5,12 (2020): e661-e671. doi:10.1016/S2468-2667(20)30185-7

[21] Qiu, Shangran et al. "Development and validation of an interpretable deep learning framework for Alzheimer's disease classification." Brain : a journal of neurology vol. 143,6 (2020): 1920-1933. doi:10.1093/brain/awaa137

[22] Glenner, G G, and C W Wong. "Alzheimer's disease: initial report of the purification and characterization of a novel cerebrovascular amyloid protein." Biochemical and biophysical research communications vol. 120,3 (1984): 885-90. doi:10.1016/s0006-291x(84)80190-4

[23] Goate, A et al. "Segregation of a missense mutation in the amyloid precursor protein gene with familial Alzheimer's disease." Nature vol. 349,6311 (1991): 704-6. doi:10.1038/349704a0

[24] Gaskin, F et al. "Human antibodies reactive with beta-amyloid protein in Alzheimer's disease." The Journal of experimental medicine vol. 177,4 (1993): 1181-6. doi:10.1084/jem.177.4.1181

[25] Suzuki, N et al. "An increased percentage of long amyloid beta protein secreted by familial amyloid beta protein precursor (beta APP717) mutants." Science (New York, N.Y.) vol. 264,5163 (1994): 1336-40. doi:10.1126/science.8191290

[26] Schützmann, Marie P et al. "Endo-lysosomal Aβ concentration and pH trigger formation of Aβ oligomers that potently induce Tau missorting." Nature communications vol. 12,1 4634. 30 Jul. 2021, doi:10.1038/s41467-021-24900-4

[27] Lesné, Sylvain et al. "A specific amyloid-beta protein assembly in the brain impairs memory." Nature vol. 440,7082 (2006): 352-7. doi:10.1038/nature04533

[28] Yang, Yang et al. "Cryo-EM structures of amyloid-β 42 filaments from human brains." Science (New York, N.Y.) vol. 375,6577 (2022): 167-172. doi:10.1126/science.abm7285

[29] Lee, Ju-Hyun et al. "Faulty autolysosome acidification in Alzheimer's disease mouse models induces autophagic build-up of Aβ in neurons, yielding senile plaques." Nature neuroscience vol. 25,6 (2022): 688-701. doi:10.1038/s41593-022-01084-8

[30] Piller, Charles. "Blots on a field?." Science (New York, N.Y.) vol. 377,6604 (2022): 358-363. doi:10.1126/science.add9993

[31] Kunkle, Brian W et al. "Genetic meta-analysis of diagnosed Alzheimer's disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing." Nature genetics vol. 51,3 (2019): 414-430. doi:10.1038/s41588-019-0358-2

[32] Teerlink, Craig C et al. "Analysis of high-risk pedigrees identifies 11 candidate variants for Alzheimer's disease." Alzheimer's & dementia : the journal of the Alzheimer's Association vol. 18,2 (2022): 307-317. doi:10.1002/alz.12397

[33] De Jager, Philip L et al. "Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci." Nature neuroscience vol. 17,9 (2014): 1156-63. doi:10.1038/nn.3786

[34] Nativio, Raffaella et al. "An integrated multi-omics approach identifies epigenetic alterations associated with Alzheimer's disease." Nature genetics vol. 52,10 (2020): 1024-1035. doi:10.1038/s41588-020-0696-0

[35] Yang, Yang et al. "NDDVD: an integrated and manually curated Neurodegenerative Diseases Variation Database." Database : the journal of biological databases and curation vol. 2018 (2018): bay018. doi:10.1093/database/bay018

[36] Kia, Demis A et al. "Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets." JAMA neurology vol. 78,4 (2021): 464-472. doi:10.1001/jamaneurol.2020.5257

[37] Yang, Yuzhe et al. "Artificial intelligence-enabled detection and assessment of Parkinson's disease using nocturnal breathing signals." Nature medicine, 10.1038/s41591-022-01932-x. 22 Aug. 2022, doi:10.1038/s41591-022-01932-x

[38] van Rheenen, Wouter et al. "Genome-wide association analyses identify new risk variants and the genetic architecture of amyotrophic lateral sclerosis." Nature genetics vol. 48,9 (2016): 1043-8. doi:10.1038/ng.3622

[39] Pun, Frank W et al. "Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics - An AI-Enabled Biological Target Discovery Platform." Frontiers in aging neuroscience vol. 14 914017. 28 Jun. 2022, doi:10.3389/fnagi.2022.914017

[40] "A novel gene containing a trinucleotide repeat that is expanded and unstable on Huntington's disease chromosomes. The Huntington's Disease Collaborative Research Group." Cell vol. 72,6 (1993): 971-83. doi:10.1016/0092-8674(93)90585-e

[41] Fang, Li et al. "LinkedSV for detection of mosaic structural variants from linked-read exome and genome sequencing data." Nature communications vol. 10,1 5585. 6 Dec. 2019, doi:10.1038/s 41467-019-13397-7

[42] Pfisterer, Ulrich et al. "Identification of epilepsy-associated neuronal subtypes and gene expression underlying epileptogenesis." Nature communications vol. 11,1 5038. 7 Oct. 2020, doi:10.1038/s41467-020-18752-7

[43] Galer, Peter D et al. "Semantic Similarity Analysis Reveals Robust Gene-Disease Relationships in Developmental and Epileptic Encephalopathies." American journal of human genetics vol. 107,4 (2020): 683-697. doi:10.1016/j.ajhg.2020.08.003

[44] Li, Jinliang et al. "Germline de novo variants in CSNK2B in Chinese patients with epilepsy." Scientific reports vol. 9,1 17909. 29 Nov. 2019, doi:10.1038/s41598-019-53484-9

[45] Daoud, Hisham, and Magdy Bayoumi. "Deep Learning Approach for Epileptic Focus Localization." IEEE transactions on biomedical circuits and systems vol. 14,2 (2020): 209-220. doi:10.1109/TBCAS.2019.2957087

[46] Macalino, Stephani Joy Y et al. "Role of computer-aided drug design in modern drug discovery." Archives of pharmacal research vol. 38,9 (2015): 1686-701. doi:10.1007/s12272-015-0640-5

[47] Sierra Bello, Omar et al. "In silico docking reveals possible Riluzole binding sites on Nav1.6 sodium channel: implications for amyotrophic lateral sclerosis therapy." Journal of theoretical biology vol. 315 (2012): 53-63. doi:10.1016/j.jtbi.2012.09.004

[48] Benavides-Serrato, Angelica et al. "Repurposing Potential of Riluzole as an ITAF Inhibitor in mTOR Therapy Resistant Glioblastoma." International journal of molecular sciences vol. 21,1 344. 5 Jan. 2020, doi:10.3390/ijms21010344

[49] Ley, Timothy J et al. "DNA sequencing of a cytogenetically normal acute myeloid lddeukaemia genome." Nature vol. 456,7218 (2008): 66-72. doi:10.1038/nature07485

[50] Tomasetti, Cristian, and Bert Vogelstein. "Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions." Science (New York, N.Y.) vol. 347,6217 (2015): 78-81. doi:10.1126/science.1260825

[51] Tomasetti, Cristian et al. "Stem cell divisions, somatic mutations, cancer etiology, and cancer prevention." Science (New York, N.Y.) vol. 355,6331 (2017): 1330-1334. doi:10.1126/science.aaf9011

[52] Martínez-Jiménez, Francisco et al. "A compendium of mutational cancer driver genes." Nature reviews. Cancer vol. 20,10 (2020): 555-572. doi:10.1038/s41568-020-0290-x

[53] Degasperi, Andrea et al. "Substitution mutational signatures in whole-genome-sequenced cancers in the UK population." Science (New York, N.Y.) vol. 376,6591 science.abl9283. 22 Apr. 2022, doi:10.1126/science.abl9283

[54] Perou, C M et al. "Molecular portraits of human breast tumours." Nature vol. 406,6797 (2000): 747-52. doi:10.1038/35021093

[55] Ali, H Raza et al. "Imaging mass cytometry and multiplatform genomics define the phenogenomic landscape of breast cancer." Nature cancer vol. 1,2 (2020): 163-175. doi:10.1038/s43018-020-0026-6

[56] Dembrower, Karin et al. "Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study." The Lancet. Digital health vol. 2,9 (2020): e468-e474. doi:10.1016/S2589-7500(20)30185-0

[57] Osako, Tomo et al. "Age-correlated protein and transcript expression in breast cancer and normal breast tissues is dominated by host endocrine effects." Nature cancer vol. 1,5 (2020): 518-532. doi:10.1038/s43018-020-0060-4

[58] Mu, Wei et al. "Non-invasive decision support for NSCLC treatment using PET/CT radiomics." Nature communications vol. 11,1 5228. 16 Oct. 2020, doi:10.1038/s41467-020-19116-x

[59] Li, Ru et al. "FOXM1 Is a Novel Molecular Target of AFP-Positive Hepatocellular Carcinoma Abrogated by Proteasome Inhibition." International journal of molecular sciences vol. 23,15 8305. 27 Jul. 2022, doi:10.3390/ijms23158305

[60] Liu, Jinping et al. "A Viral Exposure Signature Defines Early Onset of Hepatocellular Carcinoma." Cell vol. 182,2 (2020): 317-328.e10. doi:10.1016/j.cell.2020.05.038

[61] Zhang, Qiming et al. "Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma." Cell vol. 179,4 (2019): 829-845.e20. doi:10.1016/j.cell.2019.10.003

[62] Sun, Yunfan et al. "Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma." Cell vol. 184,2 (2021): 404-421.e16. doi:10.1016/j.cell.2020.11.041

[63] Finn, Richard S et al. "Phase Ib Study of Lenvatinib Plus Pembrolizumab in Patients With Unresectable Hepatocellular Carcinoma." Journal of clinical oncology : official journal of the American Society of Clinical Oncology vol. 38,26 (2020): 2960-2970. doi:10.1200/JCO.20.00808

[64] Tschandl, Philipp et al. "Human-computer collaboration for skin cancer recognition." Nature medicine vol. 26,8 (2020): 1229-1234. doi:10.1038/s41591-020-0942-0

[65] Karlsson, Joakim et al. "Molecular profiling of driver events in metastatic uveal melanoma." Nature communications vol. 11,1 1894. 20 Apr. 2020, doi:10.1038/s41467-020-15606-0

[66] Kuenzi, Brent M et al. "Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells." Cancer cell vol. 38,5 (2020): 672-684.e6. doi:10.1016/j.ccell.2020.09.014

[67] Julkunen, Heli et al. "Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects." Nature communications vol. 11,1 6136. 1 Dec. 2020, doi:10.1038/ s41467 -020-19950-z

[68] Markus, Havell et al. "Analysis of recurrently protected genomic regions in cell-free DNA found in urine." Science translational medicine vol. 13,581 (2021): eaaz3088. doi:10.1126/scitranslmed. aaz30 88

[69] Avram, Robert et al. "A digital biomarker of diabetes from smartphone-based vascular signals." Nature medicine vol. 26,10 (2020): 1576-1582. doi:10.1038/s41591-020-1010-5

[70] Vujkovic, Marijana et al. "Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis." Nature genetics vol. 52,7 (2020): 680-691. doi:10.1038/s41588-020-0637-y

[71] Dwivedi, Sanjiv K et al. "Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder." Nature communications vol. 11,1 856. 12 Feb. 2020, doi:10. 1038/s41467-020-14666-6

[72] Posma, Joram M et al. "Nutriome-metabolome relationships provide insights into dietary intake and metabolism." Nature food vol. 1,7 (2020): 426-436. doi:10.1038/s43016-020-0093-y

[73] Chandra, Vivek et al. "Promoter-interacting expression quantitative trait loci are enriched for functional genetic variants." Nature genetics vol. 53,1 (2021): 110-119. doi:10.1038/ s41588- 020- 00745-3

[74] Rhesus Macaque Genome Sequencing and Analysis Consortium et al. "Evolutionary and biomedical insights from the rhesus macaque genome." Science (New York, N.Y.) vol. 316,5822 (2007): 222-34. doi:10.1126/science.1139247

[75] Han, Lei et al. "Cell transcriptomic atlas of the non-human primate Macaca fascicularis." Nature vol. 604,7907 (2022): 723-731. doi:10.1038/s41586-022-04587-3

[76] Ginsberg, Jeremy et al. "Detecting influenza epidemics using search engine query data." Nature vol. 457,7232 (2009): 1012-4. doi:10.1038/nature07634

[77] Lazer, David et al. "Big data. The parable of Google Flu: traps in big data analysis." Science (New York, N.Y.) vol. 343,6176 (2014): 1203-5. doi:10.1126/science.1248506

[78] Metcalf, Jacob, and Kate Crawford. "Where Are Human Subjects in Big Data Research? The Emerging Ethics Divide." Big Data & Society, June 2016, doi:10.1177/2053951716650211.

[79] Dencik, L., Hintz, A., Redden, J., & Treré, E. (2019). Exploring data justice: Conceptions, applications and directions. Information, Communication and Society, 22, 873–881.