TY  - JOUR
AU  - Quaglia, Federica
AU  - Mészáros, Balint
AU  - Salladini, Edoardo
AU  - Hatos, Andras
AU  - Pancsa, Rita
AU  - Davidović, Radoslav S.
AU  - Veljković, Nevena V.
PY  - 2022
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10187
AB  - The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
T2  - Nucleic acids research
T1  - DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation
VL  - 50
IS  - D1
SP  - D480
EP  - D487
DO  - 10.1093/nar/gkab1082
ER  - 

@article{
author = "Quaglia, Federica and Mészáros, Balint and Salladini, Edoardo and Hatos, Andras and Pancsa, Rita and Davidović, Radoslav S. and Veljković, Nevena V.",
year = "2022",
abstract = "The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.",
journal = "Nucleic acids research",
title = "DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation",
volume = "50",
number = "D1",
pages = "D480-D487",
doi = "10.1093/nar/gkab1082"
}

Quaglia, F., Mészáros, B., Salladini, E., Hatos, A., Pancsa, R., Davidović, R. S.,& Veljković, N. V.. (2022). DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation. in Nucleic acids research, 50(D1), D480-D487.
https://doi.org/10.1093/nar/gkab1082

Quaglia F, Mészáros B, Salladini E, Hatos A, Pancsa R, Davidović RS, Veljković NV. DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation. in Nucleic acids research. 2022;50(D1):D480-D487.
doi:10.1093/nar/gkab1082 .

Quaglia, Federica, Mészáros, Balint, Salladini, Edoardo, Hatos, Andras, Pancsa, Rita, Davidović, Radoslav S., Veljković, Nevena V., "DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation" in Nucleic acids research, 50, no. D1 (2022):D480-D487,
https://doi.org/10.1093/nar/gkab1082 . .

TY  - JOUR
AU  - Necci, Marco
AU  - Piovesan, Damiano
AU  - Tosatto, Silvio C. E.
AU  - Davidović, Radoslav S.
AU  - Veljković, Nevena V.
PY  - 2021
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9698
AB  - Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F max = 0.483 on the full dataset and F max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.
T2  - Nature Methods
T1  - Critical assessment of protein intrinsic disorder prediction
VL  - 18
IS  - 5
SP  - 472
EP  - 481
DO  - 10.1038/s41592-021-01117-3
ER  - 

@article{
author = "Necci, Marco and Piovesan, Damiano and Tosatto, Silvio C. E. and Davidović, Radoslav S. and Veljković, Nevena V.",
year = "2021",
abstract = "Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has F max = 0.483 on the full dataset and F max = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with F max = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.",
journal = "Nature Methods",
title = "Critical assessment of protein intrinsic disorder prediction",
volume = "18",
number = "5",
pages = "472-481",
doi = "10.1038/s41592-021-01117-3"
}

Necci, M., Piovesan, D., Tosatto, S. C. E., Davidović, R. S.,& Veljković, N. V.. (2021). Critical assessment of protein intrinsic disorder prediction. in Nature Methods, 18(5), 472-481.
https://doi.org/10.1038/s41592-021-01117-3

Necci M, Piovesan D, Tosatto SCE, Davidović RS, Veljković NV. Critical assessment of protein intrinsic disorder prediction. in Nature Methods. 2021;18(5):472-481.
doi:10.1038/s41592-021-01117-3 .

Necci, Marco, Piovesan, Damiano, Tosatto, Silvio C. E., Davidović, Radoslav S., Veljković, Nevena V., "Critical assessment of protein intrinsic disorder prediction" in Nature Methods, 18, no. 5 (2021):472-481,
https://doi.org/10.1038/s41592-021-01117-3 . .