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Pregled bibliografske jedinice broj: 826451

Estimation of chance accuracy in classification structure-property models


Batista, Jadranko; Lučić, Bono
Estimation of chance accuracy in classification structure-property models // Math/Chem/Comp 2016, 28th MC2 Conference, Book of Abstracts / Vančik, Hrvoj ; Cioslowski, Jerzy (ur.).
Zagreb: -, 2016. str. 13-13 (poster, međunarodna recenzija, sažetak, znanstveni)


CROSBI ID: 826451 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Estimation of chance accuracy in classification structure-property models

Autori
Batista, Jadranko ; Lučić, Bono

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Math/Chem/Comp 2016, 28th MC2 Conference, Book of Abstracts / Vančik, Hrvoj ; Cioslowski, Jerzy - Zagreb, 2016, 13-13

Skup
Math/Chem/Comp 2016, 28th MC2 Conference

Mjesto i datum
Dubrovnik, Hrvatska, 20.06.2016. - 26.06.2016

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
classification model ; two-state model ; structure-property model ; structure prediction ; chance correlation ; membrane protein ; secondary structure

Sažetak
For each model, including classification structure-property models related to small molecules or proteins, it is possible to calculate (or to estimate by simulations) the level of accuracy is obtained with randomly generated data or by a random model. However, in generation of random data one must ensure that random data have structure and distribution similar to those of real inputs. We present the analysis of several sets of data relating to the modeling/prediction of (1) the secondary structure of membrane proteins (based on their primary structure) and (2) relationship between the structure and properties of small molecules. All these problems have two or more classes, i.e. defined and experimentally determined groups. Obtained results show that the accuracy which is obtained by chance (with randomly generated data, and/or by a random model), is determined to a large extent by the distribution of experimental input data (classes) and by the (im)partiality of the model (the total numbers of individual classes predicted by impartial model are almost the same as those in experimental data).

Izvorni jezik
Engleski

Znanstvena područja
Fizika, Kemija, Biologija



POVEZANOST RADA


Projekti:
MZO-Croatia - basic grant
Zaklada HAZU
MZOS-098-1770495-2919 - Razvoj metoda za modeliranje svojstava bioaktivnih molekula i proteina (Lučić, Bono, MZOS ) ( CroRIS)

Ustanove:
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Bono Lučić (autor)


Citiraj ovu publikaciju:

Batista, Jadranko; Lučić, Bono
Estimation of chance accuracy in classification structure-property models // Math/Chem/Comp 2016, 28th MC2 Conference, Book of Abstracts / Vančik, Hrvoj ; Cioslowski, Jerzy (ur.).
Zagreb: -, 2016. str. 13-13 (poster, međunarodna recenzija, sažetak, znanstveni)
Batista, J. & Lučić, B. (2016) Estimation of chance accuracy in classification structure-property models. U: Vančik, H. & Cioslowski, J. (ur.)Math/Chem/Comp 2016, 28th MC2 Conference, Book of Abstracts.
@article{article, author = {Batista, Jadranko and Lu\v{c}i\'{c}, Bono}, year = {2016}, pages = {13-13}, keywords = {classification model, two-state model, structure-property model, structure prediction, chance correlation, membrane protein, secondary structure}, title = {Estimation of chance accuracy in classification structure-property models}, keyword = {classification model, two-state model, structure-property model, structure prediction, chance correlation, membrane protein, secondary structure}, publisher = {-}, publisherplace = {Dubrovnik, Hrvatska} }
@article{article, author = {Batista, Jadranko and Lu\v{c}i\'{c}, Bono}, year = {2016}, pages = {13-13}, keywords = {classification model, two-state model, structure-property model, structure prediction, chance correlation, membrane protein, secondary structure}, title = {Estimation of chance accuracy in classification structure-property models}, keyword = {classification model, two-state model, structure-property model, structure prediction, chance correlation, membrane protein, secondary structure}, publisher = {-}, publisherplace = {Dubrovnik, Hrvatska} }




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