J Chem Inf Model - Ligand efficiency-based support vector regression models for predicting bioactivities of ligands to drug target proteins.

Tópicos

{ model(2341) predict(2261) use(1141) }
{ model(2656) set(1616) predict(1553) }
{ ehr(2073) health(1662) electron(1139) }
{ chang(1828) time(1643) increas(1301) }
{ design(1359) user(1324) use(1319) }
{ data(2317) use(1299) case(1017) }
{ error(1145) method(1030) estim(1020) }
{ drug(1928) target(777) effect(648) }
{ bind(1733) structur(1185) ligand(1036) }
{ compound(1573) activ(1297) structur(1058) }
{ can(981) present(881) function(850) }
{ problem(2511) optim(1539) algorithm(950) }
{ learn(2355) train(1041) set(1003) }
{ state(1844) use(1261) util(961) }
{ group(2977) signific(1463) compar(1072) }
{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ time(1939) patient(1703) rate(768) }
{ take(945) account(800) differ(722) }
{ data(1714) softwar(1251) tool(1186) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ visual(1396) interact(850) tool(830) }
{ perform(1367) use(1326) method(1137) }
{ analysi(2126) use(1163) compon(1037) }
{ high(1669) rate(1365) level(1280) }
{ use(976) code(926) identifi(902) }
{ model(3404) distribut(989) bayesian(671) }
{ can(774) often(719) complex(702) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ extract(1171) text(1153) clinic(932) }
{ general(901) number(790) one(736) }
{ howev(809) still(633) remain(590) }
{ studi(1410) differ(1259) use(1210) }
{ research(1085) discuss(1038) issu(1018) }
{ studi(1119) effect(1106) posit(819) }
{ model(3480) simul(1196) paramet(876) }
{ data(3008) multipl(1320) sourc(1022) }
{ activ(1138) subject(705) human(624) }
{ use(2086) technolog(871) perceiv(783) }
{ health(1844) social(1437) communiti(874) }
{ use(1733) differ(960) four(931) }
{ survey(1388) particip(1329) question(1065) }
{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ imag(1057) registr(996) error(939) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ concept(1167) ontolog(924) domain(897) }
{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ method(1557) propos(1049) approach(1037) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ system(1050) medic(1026) inform(1018) }
{ import(1318) role(1303) understand(862) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ monitor(1329) mobil(1314) devic(1160) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ patient(1821) servic(1111) care(1106) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

The concept of ligand efficiency (LE) indices is widely accepted throughout the drug design community and is frequently used in a retrospective manner in the process of drug development. For example, LE indices are used to investigate LE optimization processes of already-approved drugs and to re-evaluate hit compounds obtained from structure-based virtual screening methods and/or high-throughput experimental assays. However, LE indices could also be applied in a prospective manner to explore drug candidates. Here, we describe the construction of machine learning-based regression models in which LE indices are adopted as an end point and show that LE-based regression models can outperform regression models based on pIC50 values. In addition to pIC50 values traditionally used in machine learning studies based on chemogenomics data, three representative LE indices (ligand lipophilicity efficiency (LLE), binding efficiency index (BEI), and surface efficiency index (SEI)) were adopted, then used to create four types of training data. We constructed regression models by applying a support vector regression (SVR) method to the training data. In cross-validation tests of the SVR models, the LE-based SVR models showed higher correlations between the observed and predicted values than the pIC50-based models. Application tests to new data displayed that, generally, the predictive performance of SVR models follows the order SEI > BEI > LLE > pIC50. Close examination of the distributions of the activity values (pIC50, LLE, BEI, and SEI) in the training and validation data implied that the performance order of the SVR models may be ascribed to the much higher diversity of the LE-based training and validation data. In the application tests, the LE-based SVR models can offer better predictive performance of compound-protein pairs with a wider range of ligand potencies than the pIC50-based models. This finding strongly suggests that LE-based SVR models are better than pIC50-based models at predicting bioactivities of compounds that could exhibit a much higher (or lower) potency.

Resumo Limpo

concept ligand effici le indic wide accept throughout drug design communiti frequent use retrospect manner process drug develop exampl le indic use investig le optim process alreadyapprov drug reevalu hit compound obtain structurebas virtual screen method andor highthroughput experiment assay howev le indic also appli prospect manner explor drug candid describ construct machin learningbas regress model le indic adopt end point show lebas regress model can outperform regress model base pic valu addit pic valu tradit use machin learn studi base chemogenom data three repres le indic ligand lipophil effici lle bind effici index bei surfac effici index sei adopt use creat four type train data construct regress model appli support vector regress svr method train data crossvalid test svr model lebas svr model show higher correl observ predict valu picbas model applic test new data display general predict perform svr model follow order sei bei lle pic close examin distribut activ valu pic lle bei sei train valid data impli perform order svr model may ascrib much higher divers lebas train valid data applic test lebas svr model can offer better predict perform compoundprotein pair wider rang ligand potenc picbas model find strong suggest lebas svr model better picbas model predict bioactiv compound exhibit much higher lower potenc

Resumos Similares

Int J Health Geogr - Prediction of high-risk areas for visceral leishmaniasis using socioeconomic indicators and remote sensing data. ( 0,799660599765713 )
J Chem Inf Model - Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis. ( 0,765248021417814 )
Comput Math Methods Med - Variable selection in ROC regression. ( 0,740981119580367 )
Lifetime Data Anal - Understanding increments in model performance metrics. ( 0,728676492786689 )
J Chem Inf Model - Two new parameters based on distances in a receiver operating characteristic chart for the selection of classification models. ( 0,724788092022168 )
Med Decis Making - Performance of a mathematical model to forecast lives saved from HIV treatment expansion in resource-limited settings. ( 0,719747526964902 )
Comput Math Methods Med - Screening for prediabetes using machine learning models. ( 0,715600271152151 )
BMC Med Inform Decis Mak - Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population. ( 0,71454329256583 )
Int J Med Inform - Application of data mining to the identification of critical factors in patient falls using a web-based reporting system. ( 0,713590218340444 )
AMIA Annu Symp Proc - Predicting Surgical Risk: How Much Data is Enough? ( 0,710960787730492 )
J. Comput. Biol. - Prediction of siRNA potency using sparse logistic regression. ( 0,709504181309041 )
Med Decis Making - Adaptation of clinical prediction models for application in local settings. ( 0,707534573454511 )
J Med Syst - Utilization of electronic medical records to build a detection model for surveillance of healthcare-associated urinary tract infections. ( 0,70523950197448 )
Med Decis Making - A comparison of methods for converting DCE values onto the full health-dead QALY scale. ( 0,70254993809644 )
Med Decis Making - Constructing proper ROCs from ordinal response data using weighted power functions. ( 0,699978516614046 )
J Am Med Inform Assoc - An improved model for predicting postoperative nausea and vomiting in ambulatory surgery patients using physician-modifiable risk factors. ( 0,699817103323582 )
Comput Biol Chem - Using ensemble methods to deal with imbalanced data in predicting protein-protein interactions. ( 0,697486876615658 )
Appl Clin Inform - Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department. ( 0,691915262206413 )
J Chem Inf Model - Experimental and computational prediction of glass transition temperature of drugs. ( 0,690246639729977 )
Comput. Biol. Med. - A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks. ( 0,689064004898141 )
J Clin Monit Comput - Use of genetic programming, logistic regression, and artificial neural nets to predict readmission after coronary artery bypass surgery. ( 0,684892842310329 )
Neural Comput - An extension of the receiver operating characteristic curve and AUC-optimal classification. ( 0,683832250001599 )
Med Decis Making - Application of an artificial neural network to predict postinduction hypotension during general anesthesia. ( 0,683343912495492 )
BMC Med Inform Decis Mak - A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study. ( 0,678711121771822 )
J Biomed Inform - An empirical approach to model selection through validation for censored survival data. ( 0,675536620834185 )
BMC Med Inform Decis Mak - Diabetic retinopathy risk prediction for fundus examination using sparse learning: a cross-sectional study. ( 0,671310892681729 )
Comput Methods Programs Biomed - Development of a daily mortality probability prediction model from Intensive Care Unit patients using a discrete-time event history analysis. ( 0,668357810911598 )
Appl Clin Inform - Exploring the value of clinical data standards to predict hospitalization of home care patients. ( 0,667977108265812 )
BMC Med Inform Decis Mak - Bayesian predictors of very poor health related quality of life and mortality in patients with COPD. ( 0,657087705661443 )
J Chem Inf Model - Development of a computational tool to rival experts in the prediction of sites of metabolism of xenobiotics by p450s. ( 0,656759503493979 )
J Med Syst - Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models. ( 0,654161851552253 )
BMC Med Inform Decis Mak - Use of outcomes to evaluate surveillance systems for bioterrorist attacks. ( 0,650492905494264 )
J Biomed Inform - Decision-making model for early diagnosis of congestive heart failure using rough set and decision tree approaches. ( 0,649122011984978 )
Comput Math Methods Med - Modified logistic regression models using gene coexpression and clinical features to predict prostate cancer progression. ( 0,645753411762822 )
J Biomed Inform - Statistical process control for validating a classification tree model for predicting mortality--a novel approach towards temporal validation. ( 0,645579740424831 )
J Chem Inf Model - Capturing the crystal: prediction of enthalpy of sublimation, crystal lattice energy, and melting points of organic compounds. ( 0,6428813679153 )
J Biomed Inform - Towards probabilistic decision support in public health practice: predicting recent transmission of tuberculosis from patient attributes. ( 0,642746354397284 )
J Am Med Inform Assoc - Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology. ( 0,642502546340804 )
BMC Med Inform Decis Mak - Prediction of axillary lymph node metastasis in primary breast cancer patients using a decision tree-based model. ( 0,642051961716877 )
Comput. Biol. Med. - Pre-operative prediction of surgical morbidity in children: comparison of five statistical models. ( 0,642051792087562 )
Comput Biol Chem - An ensemble method for prediction of conformational B-cell epitopes from antigen sequences. ( 0,64185326936963 )
J Biomed Inform - Partial least squares and logistic regression random-effects estimates for gene selection in supervised classification of gene expression data. ( 0,641827097558674 )
Comput Methods Programs Biomed - Prediction of postprandial blood glucose under uncertainty and intra-patient variability in type 1 diabetes: a comparative study of three interval models. ( 0,640821432544608 )
J Chem Inf Model - Predictive toxicology modeling: protocols for exploring hERG classification and Tetrahymena pyriformis end point predictions. ( 0,640156037734908 )
J Med Syst - Comparison of artificial neural networks with logistic regression for detection of obesity. ( 0,639943719101508 )
J Biomed Inform - Not just data: a method for improving prediction with knowledge. ( 0,637588642455802 )
BMC Med Inform Decis Mak - Evaluation of prediction models for the staging of prostate cancer. ( 0,637009443639353 )
J Am Med Inform Assoc - A novel method of adverse event detection can accurately identify venous thromboembolisms (VTEs) from narrative electronic health record data. ( 0,635519465351414 )
J Biomed Inform - Prediction of influenza vaccination outcome by neural networks and logistic regression. ( 0,634976683848321 )
J Chem Inf Model - Homology modeling of human muscarinic acetylcholine receptors. ( 0,634773410495418 )
Comput. Biol. Med. - A ternary model of decompression sickness in rats. ( 0,632510633137782 )
Comput Math Methods Med - Prediction of BP reactivity to talking using hybrid soft computing approaches. ( 0,630959659385874 )
J Am Med Inform Assoc - Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy. ( 0,629572124594138 )
Med Decis Making - Performance profiling in primary care: does the choice of statistical model matter? ( 0,629407721540465 )
Spat Spatiotemporal Epidemiol - Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees. ( 0,629204248337659 )
Methods Inf Med - Limited sampling strategies to estimate the area under the concentration-time curve. Biases and a proposed more accurate method. ( 0,627573441329633 )
J Chem Inf Model - Using random forest to model the domain applicability of another random forest model. ( 0,625489650934382 )
IEEE J Biomed Health Inform - The effect of sample age and prediction resolution on myocardial infarction risk prediction. ( 0,625060665072442 )
Comput Methods Programs Biomed - Single stage and multistage classification models for the prediction of liver fibrosis degree in patients with chronic hepatitis C infection. ( 0,622561782703564 )
Artif Intell Med - Machine learning of clinical performance in a pancreatic cancer database. ( 0,622108406814795 )
J Med Syst - Effective automated prediction of vertebral column pathologies based on logistic model tree with SMOTE preprocessing. ( 0,621829104830558 )
BMC Med Inform Decis Mak - Non-linear dynamical signal characterization for prediction of defibrillation success through machine learning. ( 0,61620078906965 )
Comput Math Methods Med - Iterative reweighted noninteger norm regularizing SVM for gene expression data classification. ( 0,613647774974981 )
BMC Med Inform Decis Mak - Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. ( 0,613099598054017 )
J Chem Inf Model - Pragmatic approaches to using computational methods to predict xenobiotic metabolism. ( 0,611964161921325 )
Methods Inf Med - Classification of postural profiles among mouth-breathing children by learning vector quantization. ( 0,609182861103295 )
Artif Intell Med - Prediction of human major histocompatibility complex class II binding peptides by continuous kernel discrimination method. ( 0,607787477290245 )
BMC Med Inform Decis Mak - An evidential reasoning based model for diagnosis of lymph node metastasis in gastric cancer. ( 0,607501044872542 )
Comput Methods Programs Biomed - Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods. ( 0,607408976153678 )
J Med Syst - A new approach: role of data mining in prediction of survival of burn patients. ( 0,606650979816789 )
BMC Med Inform Decis Mak - Mining geriatric assessment data for in-patient fall prediction models and high-risk subgroups. ( 0,604488786408719 )
BMC Med Inform Decis Mak - Risk factors for adverse reactions from contrast agents for computed tomography. ( 0,601793636961012 )
AMIA Annu Symp Proc - Clinical risk prediction by exploring high-order feature correlations. ( 0,600762110952024 )
IEEE Trans Image Process - Network-based H.264/AVC whole frame loss visibility model and frame dropping methods. ( 0,599720254936543 )
Spat Spatiotemporal Epidemiol - Modeling habitat suitability for occurrence of highly pathogenic avian influenza virus H5N1 in domestic poultry in Asia: a spatial multicriteria decision analysis approach. ( 0,599295450496829 )
Methods Inf Med - A probabilistic model to investigate the properties of prognostic tools for falls. ( 0,595642852211352 )
J Chem Inf Model - Comparison of random forest and Pipeline Pilot Na?ve Bayes in prospective QSAR predictions. ( 0,592995656911118 )
Artif Intell Med - Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers. ( 0,592532531081014 )
BMC Med Inform Decis Mak - Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection. ( 0,591192968911961 )
Int J Health Geogr - Modelling typhoid risk in Dhaka metropolitan area of Bangladesh: the role of socio-economic and environmental factors. ( 0,591083584578831 )
AMIA Annu Symp Proc - Development and implementation of a real-time 30-day readmission predictive model. ( 0,587225560445601 )
Brief. Bioinformatics - Critical assessment of high-throughput standalone methods for secondary structure prediction. ( 0,586584304131348 )
Med Biol Eng Comput - System identification of the mechanomyogram from single motor units during voluntary isometric contraction. ( 0,586059600990889 )
J Chem Inf Model - dREL: a relational expression language for dictionary methods. ( 0,585044827907792 )
AMIA Annu Symp Proc - Clinician perspectives on the quality of patient data used for clinical decision support: a qualitative study. ( 0,581793387602909 )
J Chem Inf Model - Using information from historical high-throughput screens to predict active compounds. ( 0,581776196297361 )
Med Decis Making - Development of inpatient risk stratification models of acute kidney injury for use in electronic health records. ( 0,581545287205299 )
J Am Med Inform Assoc - From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system. ( 0,576166668383583 )
Comput Methods Programs Biomed - Exploring an optimal vector autoregressive model for multi-channel pulmonary sound data. ( 0,575697869458713 )
Int J Health Geogr - Identifying malaria vector breeding habitats with remote sensing data and terrain-based landscape indices in Zambia. ( 0,574929079689381 )
J Chem Inf Model - FAst MEtabolizer (FAME): A rapid and accurate predictor of sites of metabolism in multiple species by endogenous enzymes. ( 0,574524161752994 )
Int J Health Geogr - Application of satellite precipitation data to analyse and model arbovirus activity in the tropics. ( 0,57419696690176 )
Med Decis Making - Lehmann family of ROC curves. ( 0,573880721790417 )
Brief. Bioinformatics - Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them). ( 0,571030250291173 )
Med Biol Eng Comput - Prediction of persistence of combined evidence-based cardiovascular medications in patients with acute coronary syndrome after hospital discharge using neural networks. ( 0,568873589953296 )
J Am Med Inform Assoc - Finding falls in ambulatory care clinical documents using statistical text mining. ( 0,566913311472535 )
J Am Med Inform Assoc - Automating annotation of information-giving for analysis of clinical conversation. ( 0,566408151405127 )
BMC Med Inform Decis Mak - Decision curve analysis revisited: overall net benefit, relationships to ROC curve analysis, and application to case-control studies. ( 0,563736857744306 )
Med Decis Making - Contrasting two frameworks for ROC analysis of ordinal ratings. ( 0,56308092800473 )
AMIA Annu Symp Proc - Developing predictive models using electronic medical records: challenges and pitfalls. ( 0,561416921872822 )