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 . .

TY  - JOUR
AU  - Hatos, András
AU  - Hajdu-Soltész, Borbála
AU  - Monzon, Alexander M
AU  - Palopoli, Nicolas
AU  - Álvarez, Lucía
AU  - Aykac-Fas, Burcu
AU  - Bassot, Claudio
AU  - Benítez, Guillermo I
AU  - Bevilacqua, Martina
AU  - Chasapi, Anastasia
AU  - Chemes, Lucia
AU  - Davey, Norman E
AU  - Davidović, Radoslav S.
AU  - Dunker, A Keith
AU  - Elofsson, Arne
AU  - Gobeill, Julien
AU  - Foutel, Nicolás S González
AU  - Sudha, Govindarajan
AU  - Guharoy, Mainak
AU  - Horvath, Tamas
AU  - Iglesias, Valentin
AU  - Kajava, Andrey V.
AU  - Kovacs, Orsolya P
AU  - Lamb, John
AU  - Lambrughi, Matteo
AU  - Lazar, Tamas
AU  - Leclercq, Jeremy Y
AU  - Leonardi, Emanuela
AU  - Macedo-Ribeiro, Sandra
AU  - Macossay-Castillo, Mauricio
AU  - Maiani, Emiliano
AU  - Manso, José A
AU  - Marino-Buslje, Cristina
AU  - Martínez-Pérez, Elizabeth
AU  - Mészáros, Bálint
AU  - Mičetić, Ivan
AU  - Minervini, Giovanni
AU  - Murvai, Nikoletta
AU  - Necci, Marco
AU  - Ouzounis, Christos A
AU  - Pajkos, Mátyás
AU  - Paladin, Lisanna
AU  - Pancsa, Rita
AU  - Papaleo, Elena
AU  - Parisi, Gustavo
AU  - Pasche, Emilie
AU  - Barbosa Pereira, Pedro J
AU  - Promponas, Vasilis J
AU  - Pujols, Jordi
AU  - Quaglia, Federica
AU  - Ruch, Patrick
AU  - Salvatore, Marco
AU  - Schad, Eva
AU  - Szabo, Beata
AU  - Szaniszló, Tamás
AU  - Tamana, Stella
AU  - Tantos, Agnes
AU  - Veljković, Nevena V.
AU  - Ventura, Salvador
AU  - Vranken, Wim
AU  - Dosztányi, Zsuzsanna
AU  - Tompa, Peter
AU  - Tosatto, Silvio C E
AU  - Piovesan, Damiano
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8799
AB  - The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.
T2  - Nucleic Acids Research
T1  - DisProt: intrinsic protein disorder annotation in 2020
VL  - 48
IS  - D1
SP  - D269
EP  - D276
DO  - 10.1093/nar/gkz975
ER  - 

@article{
author = "Hatos, András and Hajdu-Soltész, Borbála and Monzon, Alexander M and Palopoli, Nicolas and Álvarez, Lucía and Aykac-Fas, Burcu and Bassot, Claudio and Benítez, Guillermo I and Bevilacqua, Martina and Chasapi, Anastasia and Chemes, Lucia and Davey, Norman E and Davidović, Radoslav S. and Dunker, A Keith and Elofsson, Arne and Gobeill, Julien and Foutel, Nicolás S González and Sudha, Govindarajan and Guharoy, Mainak and Horvath, Tamas and Iglesias, Valentin and Kajava, Andrey V. and Kovacs, Orsolya P and Lamb, John and Lambrughi, Matteo and Lazar, Tamas and Leclercq, Jeremy Y and Leonardi, Emanuela and Macedo-Ribeiro, Sandra and Macossay-Castillo, Mauricio and Maiani, Emiliano and Manso, José A and Marino-Buslje, Cristina and Martínez-Pérez, Elizabeth and Mészáros, Bálint and Mičetić, Ivan and Minervini, Giovanni and Murvai, Nikoletta and Necci, Marco and Ouzounis, Christos A and Pajkos, Mátyás and Paladin, Lisanna and Pancsa, Rita and Papaleo, Elena and Parisi, Gustavo and Pasche, Emilie and Barbosa Pereira, Pedro J and Promponas, Vasilis J and Pujols, Jordi and Quaglia, Federica and Ruch, Patrick and Salvatore, Marco and Schad, Eva and Szabo, Beata and Szaniszló, Tamás and Tamana, Stella and Tantos, Agnes and Veljković, Nevena V. and Ventura, Salvador and Vranken, Wim and Dosztányi, Zsuzsanna and Tompa, Peter and Tosatto, Silvio C E and Piovesan, Damiano",
year = "2019",
abstract = "The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.",
journal = "Nucleic Acids Research",
title = "DisProt: intrinsic protein disorder annotation in 2020",
volume = "48",
number = "D1",
pages = "D269-D276",
doi = "10.1093/nar/gkz975"
}

Hatos, A., Hajdu-Soltész, B., Monzon, A. M., Palopoli, N., Álvarez, L., Aykac-Fas, B., Bassot, C., Benítez, G. I., Bevilacqua, M., Chasapi, A., Chemes, L., Davey, N. E., Davidović, R. S., Dunker, A. K., Elofsson, A., Gobeill, J., Foutel, N. S. G., Sudha, G., Guharoy, M., Horvath, T., Iglesias, V., Kajava, A. V., Kovacs, O. P., Lamb, J., Lambrughi, M., Lazar, T., Leclercq, J. Y., Leonardi, E., Macedo-Ribeiro, S., Macossay-Castillo, M., Maiani, E., Manso, J. A., Marino-Buslje, C., Martínez-Pérez, E., Mészáros, B., Mičetić, I., Minervini, G., Murvai, N., Necci, M., Ouzounis, C. A., Pajkos, M., Paladin, L., Pancsa, R., Papaleo, E., Parisi, G., Pasche, E., Barbosa Pereira, P. J., Promponas, V. J., Pujols, J., Quaglia, F., Ruch, P., Salvatore, M., Schad, E., Szabo, B., Szaniszló, T., Tamana, S., Tantos, A., Veljković, N. V., Ventura, S., Vranken, W., Dosztányi, Z., Tompa, P., Tosatto, S. C. E.,& Piovesan, D.. (2019). DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research, 48(D1), D269-D276.
https://doi.org/10.1093/nar/gkz975

Hatos A, Hajdu-Soltész B, Monzon AM, Palopoli N, Álvarez L, Aykac-Fas B, Bassot C, Benítez GI, Bevilacqua M, Chasapi A, Chemes L, Davey NE, Davidović RS, Dunker AK, Elofsson A, Gobeill J, Foutel NSG, Sudha G, Guharoy M, Horvath T, Iglesias V, Kajava AV, Kovacs OP, Lamb J, Lambrughi M, Lazar T, Leclercq JY, Leonardi E, Macedo-Ribeiro S, Macossay-Castillo M, Maiani E, Manso JA, Marino-Buslje C, Martínez-Pérez E, Mészáros B, Mičetić I, Minervini G, Murvai N, Necci M, Ouzounis CA, Pajkos M, Paladin L, Pancsa R, Papaleo E, Parisi G, Pasche E, Barbosa Pereira PJ, Promponas VJ, Pujols J, Quaglia F, Ruch P, Salvatore M, Schad E, Szabo B, Szaniszló T, Tamana S, Tantos A, Veljković NV, Ventura S, Vranken W, Dosztányi Z, Tompa P, Tosatto SCE, Piovesan D. DisProt: intrinsic protein disorder annotation in 2020. in Nucleic Acids Research. 2019;48(D1):D269-D276.
doi:10.1093/nar/gkz975 .

Hatos, András, Hajdu-Soltész, Borbála, Monzon, Alexander M, Palopoli, Nicolas, Álvarez, Lucía, Aykac-Fas, Burcu, Bassot, Claudio, Benítez, Guillermo I, Bevilacqua, Martina, Chasapi, Anastasia, Chemes, Lucia, Davey, Norman E, Davidović, Radoslav S., Dunker, A Keith, Elofsson, Arne, Gobeill, Julien, Foutel, Nicolás S González, Sudha, Govindarajan, Guharoy, Mainak, Horvath, Tamas, Iglesias, Valentin, Kajava, Andrey V., Kovacs, Orsolya P, Lamb, John, Lambrughi, Matteo, Lazar, Tamas, Leclercq, Jeremy Y, Leonardi, Emanuela, Macedo-Ribeiro, Sandra, Macossay-Castillo, Mauricio, Maiani, Emiliano, Manso, José A, Marino-Buslje, Cristina, Martínez-Pérez, Elizabeth, Mészáros, Bálint, Mičetić, Ivan, Minervini, Giovanni, Murvai, Nikoletta, Necci, Marco, Ouzounis, Christos A, Pajkos, Mátyás, Paladin, Lisanna, Pancsa, Rita, Papaleo, Elena, Parisi, Gustavo, Pasche, Emilie, Barbosa Pereira, Pedro J, Promponas, Vasilis J, Pujols, Jordi, Quaglia, Federica, Ruch, Patrick, Salvatore, Marco, Schad, Eva, Szabo, Beata, Szaniszló, Tamás, Tamana, Stella, Tantos, Agnes, Veljković, Nevena V., Ventura, Salvador, Vranken, Wim, Dosztányi, Zsuzsanna, Tompa, Peter, Tosatto, Silvio C E, Piovesan, Damiano, "DisProt: intrinsic protein disorder annotation in 2020" in Nucleic Acids Research, 48, no. D1 (2019):D269-D276,
https://doi.org/10.1093/nar/gkz975 . .