Genius: a genetic algorithm for automated structure elucidation from 13C NMR spectra. Meiler J, Will M (2002) J Am Chem Soc 124: 1868-70 A context maintenance and retrieval model of organizational processes in free recall. Polyn SM, Norman KA, Kahana MJ (2009) Psychol Rev 116: 129-56 Coupled prediction of protein secondary and tertiary structure. Meiler J, Baker D (2003) Proc Natl Acad Sci U S A 100: 12105-10 AKAP signaling in reinstated cocaine seeking revealed by iTRAQ proteomic analysis. Reissner KJ, Uys JD, Schwacke JH, Comte-Walters S, Rutherford-Bethard JL, Dunn TE, Blumer JB, Schey KL, Kalivas PW (2011) J Neurosci 31: 5648-58 Proactive inhibitory control and attractor dynamics in countermanding action: a spiking neural circuit model. Lo CC, Boucher L, Paré M, Schall JD, Wang XJ (2009) J Neurosci 29: 9059-71 Mathematical estimates of recovery after loss of activity: II. Long-range connectivity facilitates rapid functional recovery. Hübler MJ, Buchman TG (2008) Crit Care Med 36: 489-94 Artificial neural networks improve the accuracy of cancer survival prediction. Burke HB, Goodman PH, Rosen DB, Henson DE, Weinstein JN, Harrell FE, Marks JR, Winchester DP, Bostwick DG (1997) Cancer 79: 857-62 Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment. Dasari S, Chambers MC, Martinez MA, Carpenter KL, Ham AJ, Vega-Montoto LJ, Tabb DL (2012) J Proteome Res 11: 1686-95 A multimodal neural network recruited by expertise with musical notation. Wong YK, Gauthier I (2010) J Cogn Neurosci 22: 695-713 Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis. Zhu J, Wang J, Shi Z, Franklin JL, Deane NG, Coffey RJ, Beauchamp RD, Zhang B (2013) PLoS One 8: e79282 Peripheral nerve protein expression and carbonyl content in N,N-diethlydithiocarbamate myelinopathy. Viquez OM, Valentine HL, Friedman DB, Olson SJ, Valentine WM (2007) Chem Res Toxicol 20: 370-9 Simultaneous prediction of protein secondary structure and transmembrane spans. Leman JK, Mueller R, Karakas M, Woetzel N, Meiler J (2013) Proteins 81: 1127-40 Strand-loop-strand motifs: prediction of hairpins and diverging turns in proteins. Kuhn M, Meiler J, Baker D (2004) Proteins 54: 282-8 Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign. Sliwoski G, Mendenhall J, Meiler J (2016) J Comput Aided Mol Des 30: 209-17 Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout. Mendenhall J, Meiler J (2016) J Comput Aided Mol Des 30: 177-89 Development of inpatient risk stratification models of acute kidney injury for use in electronic health records. Matheny ME, Miller RA, Ikizler TA, Waitman LR, Denny JC, Schildcrout JS, Dittus RS, Peterson JF (2010) Med Decis Making 30: 639-50 Neural networks, logistic regression, and calibration. Steyerberg EW, Harrell FE, Goodman PH (1998) Med Decis Making 18: 349-50 Discovery of 2-(2-benzoxazoyl amino)-4-aryl-5-cyanopyrimidine as negative allosteric modulators (NAMs) of metabotropic glutamate receptor 5 (mGlu₅): from an artificial neural network virtual screen to an in vivo tool compound. Mueller R, Dawson ES, Meiler J, Rodriguez AL, Chauder BA, Bates BS, Felts AS, Lamb JP, Menon UN, Jadhav SB, Kane AS, Jones CK, Gregory KJ, Niswender CM, Conn PJ, Olsen CM, Winder DG, Emmitte KA, Lindsley CW (2012) ChemMedChem 7: 406-14 Quantitative Structure-Activity Relationship Modeling of Kinase Selectivity Profiles. Kothiwale S, Borza C, Pozzi A, Meiler J (2017) Molecules 22: Benchmarking ligand-based virtual High-Throughput Screening with the PubChem database. Butkiewicz M, Lowe EW, Mueller R, Mendenhall JL, Teixeira PL, Weaver CD, Meiler J (2013) Molecules 18: 735-56 Comparison of new modeling methods for postnatal weight in ELBW infants using prenatal and postnatal data. Porcelli PJ, Rosenbloom ST (2014) J Pediatr Gastroenterol Nutr 59: e2-8 How inhibitory oscillations can train neural networks and punish competitors. Norman KA, Newman E, Detre G, Polyn S (2006) Neural Comput 18: 1577-610 Automatic detection of intracranial contours in MR images. Zijdenbos AP, Dawant BM, Margolin RA (1994) Comput Med Imaging Graph 18: 11-23 Using an artificial neural network to predict traumatic brain injury. Hale AT, Stonko DP, Lim J, Guillamondegui OD, Shannon CN, Patel MB (2018) J Neurosurg Pediatr 23: 219-226 BCL::contact-low confidence fold recognition hits boost protein contact prediction and de novo structure determination. Karakaş M, Woetzel N, Meiler J (2010) J Comput Biol 17: 153-68 Novel methods of automated structure elucidation based on 13C NMR spectroscopy. Meiler J, Köck M (2004) Magn Reson Chem 42: 1042-5
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