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Titolo:
The variable connectivity index (1)chi(f) versus the traditional moleculardescriptors: A comparative study of (1)chi(f) against descriptors of CODESSA
Autore:
Randic, M; Pompe, M;
Indirizzi:
Natl Inst Chem, Ljubljana, Slovenia Natl Inst Chem Ljubljana SloveniaNatl Inst Chem, Ljubljana, Slovenia Univ Ljubljana, Dept Chem & Chem Technol, Ljubljana 61000, Slovenia Univ Ljubljana Ljubljana Slovenia 61000 chnol, Ljubljana 61000, Slovenia
Titolo Testata:
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
fascicolo: 3, volume: 41, anno: 2001,
pagine: 631 - 638
SICI:
0095-2338(200105/06)41:3<631:TVCI(V>2.0.ZU;2-Q
Fonte:
ISI
Lingua:
ENG
Soggetto:
CHEMICAL GRAPHS; BOILING POINTS; SHAPE INDEX; PROPERTY; REGRESSIONS; INVARIANTS; LIPOPHILICITY; SIMILARITY; PARAMETERS; NUMBERS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
61
Recensione:
Indirizzi per estratti:
Indirizzo: Randic, M 3225 Kingman Rd, Ames, IA 50015 USA 3225 Kingman Rd Ames IA USA50015 ingman Rd, Ames, IA 50015 USA
Citazione:
M. Randic e M. Pompe, "The variable connectivity index (1)chi(f) versus the traditional moleculardescriptors: A comparative study of (1)chi(f) against descriptors of CODESSA", J CHEM INF, 41(3), 2001, pp. 631-638

Abstract

In this study we compared the prediction abilities of the variable connectivity index (1)chi (f) (not included in CODESSA) with topological indices available from CODESSA. We selected the boiling points of n = 100 alcohols as the property and examined the pool of 56 topological indices. Prediction capabilities of the developed models were evaluated by clasical training/test set approach. RMS errors calculated from the prediction set for the MLR models obtained from CODESSA software with 1, 2, 3, 4, and 5 parameters were 9.06, 5.69, 5.40, 4.9, and 3.37 degreesC, respectively. Using the variable connectivity index with weights x = 0.10 and y = -0.92 for carbon and oxygen atom respectively, we obtain regression BP = 38.12 (1)chi (f) - 37.56 with the correlation coefficient r = 0.9915, RMS error 4.21 degreesC calculated from the test set, and Fisher ratio F = 5691. Prediction capability of the variable connectivity index was better than for MLR regression model with up to four parameters.

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Documento generato il 07/04/20 alle ore 02:09:20