[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123598-en":3,"doc-seo-123598-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123598,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","High Accuracy Protein Identification - Fusion of solid-state nanopore sensing and machine learning - Abstract","Proteins serve as key biomarkers in health diagnostics, yet identifying proteins of similar size remains difficult using label-free solid-state nanopore sensing. This work integrates solid-state nanopore sensing with machine learning to improve protein identification accuracy. Four similarly sized proteins are analyzed using nanopore instruments with 100 kHz (200 ksps) and 10 MHz (40 Msps) bandwidths, achieving F-scores up to 65.9% and 83.2%. Advanced clustering and ML on event features further raise performance, reaching up to 88.7% F-value and 96.4% specificity for combinations of four proteins.","High Accuracy Protein Identification: Fusion of solid-state nanopore  \nsensing and machine learning  \nShankar Dutt1, γ, *, Hancheng Shao 1, γ, Buddini Karawdeniya2, Y. M. Nuwan D. Y. Bandara3, Elena Daskalaki4, Hanna Suominen4,5, Patrick Kluth 1  \n1Department of Materials Physics, Research School of Physics, Australian National University, Canberra ACT 2601, Australia  \n2Department of Electronic Materials Engineering, Research School of Physics, Australian National University, Canberra ACT 2601, Australia  \n3Research School of Chemistry, Australian National University, Canberra ACT 2601,  \nAustralia  \n4School of Computing, College of Engineering, Computing and Cybernetics, Australian National University, Canberra ACT 2601, Australia  \n5Eccles Institute of Neuroscience, College of Health and Medicine, Australian National  \nUniversity, Canberra ACT 2601, Australia  \nγ: These authors contributed equally.  \n*Email: [shankar.dutt@anu.edu.au](shankar.dutt@anu.edu.au)  \nABSTRACT  \nProteins are arguably the most important class of biomarkers for health diagnostic purposes. Label-free solid-state nanopore sensing is a versatile technique for sensing and analysing biomolecules such as proteins at single-molecule level. While molecular-level information on size, shape, and charge of proteins can be assessed by nanopores, the identification of proteins with comparable sizes remains a challenge. Here, we present methods that combine solid-state nanopore sensing with machine learning to address this challenge. We assess the translocationsof four similarly sized proteins using amplifiers with bandwidths (BWs) of 100 kHz (sampling rate=200 ksps) and 10 MHz (sampling rate=40 Msps), the highest bandwidth reported for protein sensing, using nanopores fabricated in \u003C10 nm thick silicon nitride membranes. Fvalues of up to 65.9% and 83.2%(without clustering of the protein signals) were achieved with 100 kHz and 10 MHz BW instruments, respectively, for identification of the four proteins. The accuracy of protein identification was significantly improved by grouping the signals into several clusters depending on the event features, resulting in F-value and specificity reaching as high as 88.7% and 96.4%, respectively, for combinations of four proteins. The combined improvement in sensor signals through the use of high bandwidth instruments, advanced clustering, machine learning, and other advanced data analysis methods allows identification of proteins with high accuracy.  \n1. INTRODUCTION  \nProteins are the vital building blocks of life, orchestrating a vast array of biological functions and processes that maintain health and critical cellular functions. They can serve as biomarkers for diagnosis and monitoring of diseases, facilitate cellular signaling and reaction catalysis, and enable transport and storage of critical ions and molecules 1–6. Proteins are constructed of amino acid chains folded into specific tertiary and quaternary structures that govern their function. While proteins are vital actors for biological processes and functions essential for life, their presence or fluctuations of their typical levels can also indicate detrimental biological processes such as adverse health conditions. In some circumstances, proteins contribute to the advancement of diseases by intensifying their activity to create favorable settings that enhance the progression of the disease, e.g. proteins such as PADI4 and HIF-1 facilitate the growth of cancer7–9. Irrespective of the function, selective protein detection and quantification is critical for the identification, evaluation and understanding of biological processes and related progress, e.g., for future drug development.  \nComplex biological samples like serum, saliva, or urine contain a multitude of protein biomarkers indicative of a host of health conditions. There are numerous conventional analytical methods for protein detection, characterization, and quantification such as mass spectrometry (MS) 10,","cbCairlWBjz7nhq6","https://ap.wps.com/l/cbCairlWBjz7nhq6","pdf",17681291,1,70,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"Why is protein identification with solid-state nanopore sensing challenging?\",\"answer\":\"Proteins with comparable sizes can generate similar signals, making discrimination difficult despite nanopores providing size, shape, and charge-related information.\"},{\"question\":\"How does the study improve accuracy when identifying four similarly sized proteins?\",\"answer\":\"It combines high-bandwidth solid-state nanopore sensing with machine learning and event-feature clustering to group signals into separate clusters before classification.\"},{\"question\":\"What performance was achieved with different instrument bandwidths?\",\"answer\":\"Using 100 kHz bandwidth (200 ksps) achieved F-values up to 65.9%, while 10 MHz bandwidth (40 Msps) achieved up to 83.2% without clustering; with clustering and ML, F-value reached as high as 88.7% and specificity up to 96.4%.\"}]","High Accuracy Protein Identification - Fusion of solid-state nanopore sensing and machine learning - Abstract | PDF",1785817567,176,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"high-accuracy-protein-identification-fusion-of-solid-state-nanopore-sensing-and-machine-learning-abstract","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/high-accuracy-protein-identification-fusion-of-solid-state-nanopore-sensing-and-machine-learning-abstract/123598/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is protein identification with solid-state nanopore sensing challenging?","Question",{"text":75,"@type":76},"Proteins with comparable sizes can generate similar signals, making discrimination difficult despite nanopores providing size, shape, and charge-related information.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the study improve accuracy when identifying four similarly sized proteins?",{"text":80,"@type":76},"It combines high-bandwidth solid-state nanopore sensing with machine learning and event-feature clustering to group signals into separate clusters before classification.",{"name":82,"@type":73,"acceptedAnswer":83},"What performance was achieved with different instrument bandwidths?",{"text":84,"@type":76},"Using 100 kHz bandwidth (200 ksps) achieved F-values up to 65.9%, while 10 MHz bandwidth (40 Msps) achieved up to 83.2% without clustering; with clustering and ML, F-value reached as high as 88.7% and specificity up to 96.4%.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,104,109,114,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":21,"slug":103},"Exam","exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":105,"slug":137},19,"General","general"]