CoChat
Sign Up
Cited by 107

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Biolayer interferometry and its applications in drug discovery and development

Jug, Ana, Bratkovič, Tomaž, Ilaš, Janez·2024·TrAC Trends in Analytical Chemistry
DOI 10.1016/j.trac.2024.117741
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.trac.2024.117741

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • We were unable to calculate an exact binding affinity for the interaction between Lp(a) and LDLR.

    “We were unable to calculate an exact binding affinity for the interaction between Lp(a) and LDLR, a known limitation of BLI for moderate to weak affinity interactions and analyte concentrations below the Kd84.”

    From Functional interrogation of cellular Lp(a) uptake by genome-scale CRISPR screening (2025) · cites this paper as [84]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 110

  1. Fechner, 2022, Through the looking-glass - recent developments in reflectometry open new possibilities for biosensor applications, TrAC Trends Anal. Chem. (Reference Ed.), 156
  2. Cooper, 2002, Optical biosensors in drug discovery, Nat. Rev. Drug Discov., 1, 515, 10.1038/nrd838 · DOI
  3. Ullah, 2022, An experimental framework for developing point-of-need biosensors: connecting bio-layer interferometry and electrochemical impedance spectroscopy, Biosensors, 12, 938, 10.3390/bios12110938 · DOI
  4. Ribeiro, 2022, Electrochemistry combined-surface plasmon resonance biosensors: a review, TrAC Trends Anal. Chem. (Reference Ed.), 157
  5. Renaud, 2016, Biophysics in drug discovery: impact, challenges and opportunities, Nat. Rev. Drug Discov., 15, 679, 10.1038/nrd.2016.123 · DOI
  6. Copeland, 2010, The dynamics of drug-target interactions: drug-target residence time and its impact on efficacy and safety, Expet Opin. Drug Discov., 5, 305, 10.1517/17460441003677725 · DOI
  7. Copeland, 2016, The drug–target residence time model: a 10-year retrospective, Nat. Rev. Drug Discov., 15, 87, 10.1038/nrd.2015.18 · DOI
  8. De Arriba, 1996, In vitro pharmacological characterization of a new selective angiotensin AT1 receptor antagonist, UR-7280, Eur. J. Pharmacol., 318, 341, 10.1016/S0014-2999(96)00794-7 · DOI
  9. Georgi, 2018, Binding kinetics survey of the drugged kinome, J. Am. Chem. Soc., 140, 15774, 10.1021/jacs.8b08048 · DOI
  10. Swinney, 2006, Biochemical mechanisms of new molecular entities (NMEs) approved by United States FDA during 2001-2004: mechanisms leading to optimal efficacy and safety, Curr. Top. Med. Chem., 6, 461, 10.2174/156802606776743093 · DOI
  11. Vauquelin, 2006, Slow antagonist dissociation and long-lasting in vivo receptor protection, Trends Pharmacol. Sci., 27, 355, 10.1016/j.tips.2006.05.001 · DOI
  12. Borkin, 2018, Complexity of blocking bivalent protein–protein interactions: development of a highly potent inhibitor of the menin–mixed-lineage leukemia interaction, J. Med. Chem., 61, 4832, 10.1021/acs.jmedchem.8b00071 · DOI
  13. Nguyen, 2015, Surface plasmon resonance: a versatile technique for biosensor applications, Sensors, 15, 10481, 10.3390/s150510481 · DOI
  14. Capelli, 2023, Surface plasmon resonance technology: recent advances, applications and experimental cases, TrAC Trends Anal. Chem. (Reference Ed.), 163
  15. Concepcion, 2009, Label-free detection of biomolecular interactions using BioLayer interferometry for kinetic characterization, Comb. Chem. High Throughput Screen., 12, 791, 10.2174/138620709789104915 · DOI
  16. Williford, 2023, Structure-based design of bisubstrate tetracycline destructase inhibitors that block flavin redox cycling, J. Med. Chem., 66, 3917, 10.1021/acs.jmedchem.2c01629 · DOI
  17. Marchand, 2023, Rational design of chemically controlled antibodies and protein therapeutics, ACS Chem. Biol., 18, 1259, 10.1021/acschembio.3c00012 · DOI
  18. Hernandez, 2011, Control of protein immobilization: coupling immobilization and site-directed mutagenesis to improve biocatalyst or biosensor performance, Enzym. Microb. Technol., 48, 107, 10.1016/j.enzmictec.2010.10.003 · DOI
  19. Koshland, 1963, Correlation of structure and function in enzyme action: theoretical and experimental tools are leading to correlations between enzyme structure and function, Science, 142, 1533, 10.1126/science.142.3599.1533 · DOI
  20. Lou, 2016, Determining functional aptamer‐protein interaction by biolayer interferometry, Curr. Protoc. Nucleic Acid Chem., 67, 10.1002/cpnc.18 · DOI
  21. Rainard, 2018, Using microscale thermophoresis to characterize hits from high-throughput screening: a European lead factory perspective, SLAS Discov, 23, 225, 10.1177/2472555217744728 · DOI
  22. Esposito, 2023, Targeted systematic evolution of an RNA platform neutralizing DNMT1 function and controlling DNA methylation, Nat. Commun., 14, 99, 10.1038/s41467-022-35222-4 · DOI
  23. Abdiche, 2008, Determining kinetics and affinities of protein interactions using a parallel real-time label-free biosensor, the Octet, Anal. Biochem., 377, 209, 10.1016/j.ab.2008.03.035 · DOI
  24. Cochran, 2009, Surface plasmon resonance-based solution affinity assay for heparan sulfate-binding proteins, Glycoconj. J., 26, 577, 10.1007/s10719-008-9210-0 · DOI
  25. Vignon, 2020, Direct detection of low-molecular-weight compounds in 2D and 3D aptasensors by biolayer interferometry, ACS Sens., 5, 2326, 10.1021/acssensors.0c00925 · DOI
  26. Swartz, 2018, Rapid quantification of monoclonal antibody titer in cell culture harvests by antibody-induced Z-ELP-E2 nanoparticle cross-linking, Anal. Chem., 90, 14447, 10.1021/acs.analchem.8b04083 · DOI
  27. Wallner, 2019, Lectin bio‐layer interferometry for assessing product quality of Fc‐ glycosylated immunoglobulin G, Biotechnol. Prog., 35, 10.1002/btpr.2864 · DOI
  28. Cannon, 2004, Comparative analyses of a small molecule/enzyme interaction by multiple users of Biacore technology, Anal. Biochem., 330, 98, 10.1016/j.ab.2004.02.027 · DOI
  29. Feng, 2023, Microfluidic trends in drug screening and drug delivery, TrAC Trends Anal. Chem. (Reference Ed.), 158
  30. Li, 2021, Drug screening strategies using metal-based luminescent probes, TrAC Trends Anal. Chem. (Reference Ed.), 139
  31. Wartchow, 2011, Biosensor-based small molecule fragment screening with biolayer interferometry, J. Comput. Aided Mol. Des., 25, 669, 10.1007/s10822-011-9439-8 · DOI
  32. Overacker, 2021, Biolayer interferometry provides a robust method for detecting DNA binding small molecules in microbial extracts, Anal. Bioanal. Chem., 413, 1159, 10.1007/s00216-020-03079-5 · DOI
  33. Zhang, 2021, Automated affinity selection for rapid discovery of peptide binders, Chem. Sci., 12, 10817, 10.1039/D1SC02587B · DOI
  34. Bothe, 2022, Fragment screening using biolayer interferometry reveals ligands targeting the SHP-motif binding site of the AAA+ ATPase P97, Commun. Chem., 5, 169, 10.1038/s42004-022-00782-5 · DOI
  35. Chimenti, 2015, A fragment-based ligand screen against part of a large protein machine: the ND1 domains of the AAA+ ATPase P97/VCP, SLAS Discov, 20, 788, 10.1177/1087057115570550 · DOI
  36. Wright, 2017, Structure-based optimization and synthesis of antiviral drug arbidol analogues with significantly improved affinity to influenza hemagglutinin, Bioorg. Med. Chem. Lett., 27, 3744, 10.1016/j.bmcl.2017.06.074 · DOI
  37. Munuganti, 2013, Targeting the binding function 3 (BF3) site of the androgen receptor through virtual screening. 2. Development of 2-((2-phenoxyethyl) thio)-1 H -benzimidazole derivatives, J. Med. Chem., 56, 1136, 10.1021/jm3015712 · DOI
  38. Kump, 2020, Discovery and characterization of 2,5-substituted benzoic acid dual inhibitors of the anti-apoptotic mcl-1 and bfl-1 proteins, J. Med. Chem., 63, 2489, 10.1021/acs.jmedchem.9b01442 · DOI
  39. Roy, 2023, De novo design of highly selective miniprotein inhibitors of integrins Αvβ6 and Αvβ8, Nat. Commun., 14, 5660, 10.1038/s41467-023-41272-z · DOI
  40. Simon, 2019, Cofactor analogues as active site probes in lysine acetyltransferases, J. Med. Chem., 62, 2582, 10.1021/acs.jmedchem.8b01887 · DOI
  41. Huggins, 2012, Rational approaches to improving selectivity in drug design, J. Med. Chem., 55, 1424, 10.1021/jm2010332 · DOI
  42. Li, 2022, Structure-based discovery and optimization of furo[3,2- c ]Pyridin-4(5 H)One derivatives as potent and second bromodomain (BD2)-Selective bromo and extra terminal domain (BET) inhibitors, J. Med. Chem., 65, 5760, 10.1021/acs.jmedchem.2c00100 · DOI
  43. Ran, 2015, Structure-based design of γ-carboline analogues as potent and specific BET bromodomain inhibitors, J. Med. Chem., 58, 4927, 10.1021/acs.jmedchem.5b00613 · DOI
  44. Dai, 2021, Development of novel tetrahydroquinoline inhibitors of NLRP3 inflammasome for potential treatment of DSS-induced mouse colitis, J. Med. Chem., 64, 871, 10.1021/acs.jmedchem.0c01924 · DOI
  45. Chen, 2023, Development of orally bioavailable amidobenzimidazole analogues targeting stimulator of interferon gene (STING) receptor, J. Med. Chem., 66, 5584, 10.1021/acs.jmedchem.2c02046 · DOI
  46. Zhang, 2018, Site‐selective cysteine–cyclooctyne conjugation, Angew. Chem. Int. Ed., 57, 6459, 10.1002/anie.201800860 · DOI
  47. Schiedel, 2016, Structure-based development of an affinity probe for sirtuin 2, Angew. Chem. Int. Ed., 55, 2252, 10.1002/anie.201509843 · DOI
  48. Gowthaman, 2016, DARC: mapping surface topography by ray-casting for effective virtual screening at protein interaction sites, J. Med. Chem., 59, 4152, 10.1021/acs.jmedchem.5b00150 · DOI
  49. Jiang, 2014, Discovery of potent keap1–nrf 2 protein–protein interaction inhibitor based on molecular binding determinants analysis, J. Med. Chem., 57, 2736, 10.1021/jm5000529 · DOI
  50. Jiang, 2016, Discovery and development of kelch-like ECH-associated protein 1. Nuclear factor erythroid 2-related factor 2 (KEAP1:NRF2) protein–protein interaction inhibitors: achievements, challenges, and future directions, J. Med. Chem., 59, 10837, 10.1021/acs.jmedchem.6b00586 · DOI
  51. Durdagi, 2012, Protein–protein interactions: inhibition of mammalian carbonic anhydrases I–xv by the murine inhibitor of carbonic anhydrase and other members of the transferrin family, J. Med. Chem., 55, 5529, 10.1021/jm3004587 · DOI
  52. Orthwein, 2021, Kinetic analysis of a protein-protein complex to determine its dissociation constant (KD) and the effective concentration (EC50) of an interplaying effector molecule using bio-layer interferometry, BIO-Protoc., 11, 10.21769/BioProtoc.4152 · DOI
  53. Cao, 2022, Design of protein-binding proteins from the target structure alone, Nature, 605, 551, 10.1038/s41586-022-04654-9 · DOI · Paper page
  54. Gainza, 2023, De novo design of protein interactions with learned surface fingerprints, Nature, 617, 176, 10.1038/s41586-023-05993-x · DOI
  55. Bai, 2019, A potent and selective small-molecule degrader of STAT3 achieves complete tumor regression in vivo, Cancer Cell, 36, 498, 10.1016/j.ccell.2019.10.002 · DOI · Paper page
  56. Bollu, 2022, Identification and characterization of a novel indoleamine 2,3-dioxygenase 1 protein degrader for glioblastoma, J. Med. Chem., 65, 15642, 10.1021/acs.jmedchem.2c00771 · DOI
  57. Silva, 2019, Targeted degradation of aberrant tau in frontotemporal dementia patient-derived neuronal cell models, Elife, 8, 10.7554/eLife.45457 · DOI · Paper page
  58. Yang, 2022, Discovery of a highly potent and selective dual PROTAC degrader of CDK12 and CDK13, J. Med. Chem., 65, 11066, 10.1021/acs.jmedchem.2c00384 · DOI
  59. Liu, 2020, Assays and technologies for developing proteolysis targeting chimera degraders, Future Med. Chem.
  60. Ward, 2023, Biophysical and computational approaches to study ternary complexes: a ‘cooperative relationship’ to rationalize targeted protein degradation, Chembiochem, 24, 10.1002/cbic.202300163 · DOI
  61. Schiemer, 2021, Snapshots and ensembles of BTK and cIAP1 protein degrader ternary complexes, Nat. Chem. Biol., 17, 152, 10.1038/s41589-020-00686-2 · DOI · Paper page
  62. Childs-Disney, 2022, Targeting RNA structures with small molecules, Nat. Rev. Drug Discov., 21, 736, 10.1038/s41573-022-00521-4 · DOI
  63. Shino, 2023, Probing RNA–small molecule interactions using biophysical and computational approaches, ACS Chem. Biol., 18, 2368, 10.1021/acschembio.3c00287 · DOI
  64. Wang, 2019, The hairpin form of r(G4C2)Exp in c9ALS/FTD is repeat-associated non-ATG translated and a target for bioactive small molecules, Cell Chem. Biol., 26, 179, 10.1016/j.chembiol.2018.10.018 · DOI
  65. Yang, 2016, Small molecule recognition and tools to study modulation of r(CGG) exp in fragile X-associated tremor ataxia syndrome, ACS Chem. Biol., 11, 2456, 10.1021/acschembio.6b00147 · DOI
  66. Dai, 2022, Target fishing reveals a novel mechanism of 1,2,4-oxadiazole derivatives targeting Rpn6, a subunit of 26S proteasome, J. Med. Chem., 65, 5029, 10.1021/acs.jmedchem.1c02210 · DOI
  67. Jiang, 2023, High-throughput mass spectrometry imaging of biological systems: current approaches and future directions, TrAC Trends Anal. Chem. (Reference Ed.), 163
  68. Jung, 2022, BLI‐MS: combining biolayer interferometry and mass spectrometry, Proteomics, 22, 10.1002/pmic.202100031 · DOI
  69. Luo, 2023, Microprobe-capture in-emitter elution: an affinity capture technique to directly couple a label-free optical sensing technology with mass spectrometry for protein analysis, Anal. Chem., 95, 5494, 10.1021/acs.analchem.2c04727 · DOI
  70. Luo, 2023, Study of β1-transferrin and β2-transferrin using microprobe-capture in-emitter elution and high-resolution mass spectrometry, Sci. Rep., 13, 10.1038/s41598-023-42064-7 · DOI
  71. Dong, 2023, Structure-based design of the indole-substituted triazolopyrimidines as new eed–H3K27me3 inhibitors for the treatment of lymphoma, J. Med. Chem., 66, 1063, 10.1021/acs.jmedchem.2c02028 · DOI
  72. Fagan, 2019, A chemical probe for tudor domain protein Spindlin1 to investigate chromatin function, J. Med. Chem., 62, 9008, 10.1021/acs.jmedchem.9b00562 · DOI
  73. Gao, 2021, Discovery and biological evaluation of a small‐molecule inhibitor of CRM1 that suppresses the growth of triple‐negative breast cancer cells, Traffic, 22, 221, 10.1111/tra.12802 · DOI
  74. Guo, 2020, Synthesis and biological evaluation of B-cell lymphoma 6 inhibitors of N -Phenyl-4-Pyrimidinamine derivatives bearing potent activities against tumor growth, J. Med. Chem., 63, 676, 10.1021/acs.jmedchem.9b01618 · DOI
  75. Matias-Barrios, 2021, Discovery of new catalytic topoisomerase II inhibitors for anticancer therapeutics, Front. Oncol., 10, 10.3389/fonc.2020.633142 · DOI
  76. He, 2022, Discovery of potent and selective 2-(Benzylthio)Pyrimidine-based DCN1-UBC12 inhibitors for anticardiac fibrotic effects, J. Med. Chem., 65, 163, 10.1021/acs.jmedchem.1c01207 · DOI
  77. Lu, 2019, Enhanced inhibition of influenza A virus adhesion by di- and trivalent hemagglutinin inhibitors, J. Med. Chem., 62, 6398, 10.1021/acs.jmedchem.9b00303 · DOI
  78. Wei, 2022, Preventing influenza A virus infection by mixed inhibition of neuraminidase and hemagglutinin by divalent inhibitors, J. Med. Chem., 65, 7312, 10.1021/acs.jmedchem.2c00319 · DOI
  79. Han, 2012, Lead optimization studies on FimH antagonists: discovery of potent and orally bioavailable ortho-substituted biphenyl mannosides, J. Med. Chem., 55, 3945, 10.1021/jm300165m · DOI
  80. Jbara, 2021, Engineering bioactive dimeric transcription factor analogs via palladium rebound reagents, J. Am. Chem. Soc., 143, 11788, 10.1021/jacs.1c05666 · DOI
  81. Do, 2008, A rapid method for determining dynamic binding capacity of resins for the purification of proteins, Protein Expr. Purif., 60, 147, 10.1016/j.pep.2008.04.009 · DOI
  82. Swartz, 2018, Rapid quantification of monoclonal antibody titer in cell culture harvests by antibody-induced Z-ELP-E2 nanoparticle cross-linking, Anal. Chem., 90, 14447, 10.1021/acs.analchem.8b04083 · DOI
  83. Wallner, 2019, Lectin bio‐layer interferometry for assessing product quality of Fc‐ glycosylated immunoglobulin G, Biotechnol. Prog., 35, 10.1002/btpr.2864 · DOI
  84. Lad, 2015, High-throughput kinetic screening of hybridomas to identify high-affinity antibodies using bio-layer interferometry, SLAS Discov, 20, 498, 10.1177/1087057114560123 · DOI
  85. Abdiche, 2014, High-throughput epitope binning assays on label-free array-based biosensors can yield exquisite epitope discrimination that facilitates the selection of monoclonal antibodies with functional activity, PLoS One, 9, 10.1371/journal.pone.0092451 · DOI
  86. Nagashima, 2023, Epitope binning of monoclonal and polyclonal antibodies by biolayer interferometry, vol. 2673, 17
  87. Noy-Porat, 2021, Characterization of antibody-antigen interactions using biolayer interferometry, STAR Protoc., 2, 10.1016/j.xpro.2021.100836 · DOI
  88. Sakashita, 2022, Advanced hybridoma technology for selective production of high-affinity monoclonal antibodies through B-cell receptors, J. Immunol. Methods, 511, 10.1016/j.jim.2022.113384 · DOI
  89. Li, 2023, A tool for evaluating heterogeneity in avidity of polyclonal antibodies, Front. Immunol., 14
  90. Trabjerg, 2018, Conformational analysis of complex protein states by hydrogen/deuterium exchange mass spectrometry (HDX-MS): challenges and emerging solutions, TrAC Trends Anal. Chem. (Reference Ed.), 106, 125, 10.1016/j.trac.2018.06.008 · DOI
  91. Guo, 2018, Biosensor-based epitope mapping of antibodies targeting the hemagglutinin and neuraminidase of influenza A virus, J. Immunol. Methods, 461, 23, 10.1016/j.jim.2018.07.007 · DOI
  92. Akbarian, 2022, Instability challenges and stabilization strategies of pharmaceutical proteins, Pharmaceutics, 14, 2533, 10.3390/pharmaceutics14112533 · DOI
  93. Zhong, 2013, Biological insights into therapeutic protein modifications throughout trafficking and their biopharmaceutical applications, Int. J. Cell Biol., 1, 10.1155/2013/273086 · DOI
  94. Van Der Burg, 2023, Recent capillary electrophoresis applications for upstream and downstream biopharmaceutical process monitoring, TrAC Trends Anal. Chem. (Reference Ed.), 160
  95. Mastrangeli, 2019, Glycoengineered antibodies: towards the next-generation of immunotherapeutics, Glycobiology, 29, 199, 10.1093/glycob/cwy092 · DOI
  96. Chung, 2014, Identification of antibody glycosylation structures that predict monoclonal antibody fc-effector function, AIDS, 28, 2523, 10.1097/QAD.0000000000000444 · DOI
  97. Stracke, 2014, A novel approach to investigate the effect of methionine oxidation on pharmacokinetic properties of therapeutic antibodies, mAbs, 6, 1229, 10.4161/mabs.29601 · DOI
  98. Cymer, 2017, Oxidation of M252 but not M428 in hu-IgG1 is responsible for decreased binding to and activation of hu-FcγRIIa (His 131), Biologicals, 50, 125, 10.1016/j.biologicals.2017.09.006 · DOI
  99. Bajardi-Taccioli, 2015, Effect of protein aggregates on characterization of FcRn binding of fc-fusion therapeutics, Mol. Immunol., 67, 616, 10.1016/j.molimm.2015.06.031 · DOI
  100. Bajardi-Taccioli, 2020, Biolayer interferometry-based FcγRIIa binding assay for a therapeutic antibody with strong effector function, Anal. Biochem., 611, 10.1016/j.ab.2020.113842 · DOI
  101. Neuber, 2014, Characterization and screening of IgG binding to the neonatal Fc receptor, mAbs, 6, 928, 10.4161/mabs.28744 · DOI
  102. Souders, 2015, A novel in vitro assay to predict neonatal Fc receptor-mediated human IgG half-life, mAbs, 7, 912, 10.1080/19420862.2015.1054585 · DOI
  103. Zhou, 2018, Characterization of antibody-C1q interactions by biolayer interferometry, Anal. Biochem., 549, 143, 10.1016/j.ab.2018.03.022 · DOI
  104. Prang, 2005, Cellular and complement-dependent cytotoxicity of ep-CAM-specific monoclonal antibody MT201 against breast cancer cell lines, Br. J. Cancer, 92, 342, 10.1038/sj.bjc.6602310 · DOI
  105. Mitoma, 2008, Mechanisms for cytotoxic effects of anti–tumor necrosis factor agents on transmembrane tumor necrosis factor α–expressing cells: comparison among infliximab, etanercept, and adalimumab, Arthritis Rheum., 58, 1248, 10.1002/art.23447 · DOI
  106. Matucci, 2021, Immunogenicity-unwanted immune responses to biological drugs – can we predict them?, Expet Rev. Clin. Pharmacol., 14, 47, 10.1080/17512433.2020.1772053 · DOI
  107. Lotz, 2022, When to extend monitoring of anti-drug antibodies for high-risk biotherapeutics in clinical trials: an opinion from the European immunogenicity platform, AAPS J., 24, 68, 10.1208/s12248-022-00712-2 · DOI
  108. Shibata, 2018, Comparison of different immunoassay methods to detect human anti-drug antibody using the WHO erythropoietin antibody reference panel for analytes, J. Immunol. Methods, 452, 73, 10.1016/j.jim.2017.09.009 · DOI
  109. Suzuki, 2020, Development of anti-drug monoclonal antibody panels against adalimumab and infliximab, Biologicals, 63, 39, 10.1016/j.biologicals.2019.12.003 · DOI
  110. Tada, 2018, Development and characterization of an anti-rituximab monoclonal antibody panel, mAbs, 10, 370, 10.1080/19420862.2018.1424610 · DOI

Cited by

Sorted by citations

Metadata

Authors
Jug, A., Bratkovič, T., & Ilaš, J.
ORCID
Ilaš, Janez
Venue
TrAC Trends in Analytical Chemistry
Publisher
Elsevier BV
Published
2024-07
Volume
176
Pages
117741
ISSN
0165-9936
DOI
10.1016/j.trac.2024.117741
Cited by
107
References
6
Language
en
Licence
Funders
ARRS (P1-0208, P1-0420)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review