Citations (132)
Keep up to date with the latest research on this topic with citation updates for this article.
Read on this site (8)
Bi Zhao & Lukasz Kurgan. (2021) Surveying over 100 predictors of intrinsic disorder in proteins. Expert Review of Proteomics 18:12, pages 1019-1029.
Read now
Read now
Eshel Faraggi, A. Keith Dunker, Joel L. Sussman & Andrzej Kloczkowski. (2018) Comparing NMR and X-ray protein structure: Lindemann-like parameters and NMR disorder. Journal of Biomolecular Structure and Dynamics 36:9, pages 2331-2341.
Read now
Read now
Philippe Lieutaud, François Ferron, Alexey V. Uversky, Lukasz Kurgan, Vladimir N. Uversky & Sonia Longhi. (2016) How disordered is my protein and what is its disorder for? A guide through the “dark side” of the protein universe. Intrinsically Disordered Proteins 4:1.
Read now
Read now
Lumbini R. Yadav, Sharad Rai, M.V. Hosur & Ashok K. Varma. (2015) Functional assessment of intrinsic disorder central domains of BRCA1. Journal of Biomolecular Structure and Dynamics 33:11, pages 2469-2478.
Read now
Read now
Shelly DeForte, Krishna D Reddy & Vladimir N Uversky. (2015) Digested disorder, Quarterly intrinsic disorder digest (October-November-December, 2013). Intrinsically Disordered Proteins 3:1.
Read now
Read now
Xiao Fan & Lukasz Kurgan. (2014) Accurate prediction of disorder in protein chains with a comprehensive and empirically designed consensus. Journal of Biomolecular Structure and Dynamics 32:3, pages 448-464.
Read now
Read now
Michail
Yu Lobanov, Igor
V. Sokolovskiy & Oxana
V. Galzitskaya. (2013) IsUnstruct: prediction of the residue status to be ordered or disordered in the protein chain by a method based on the Ising model. Journal of Biomolecular Structure and Dynamics 31:10, pages 1034-1043.
Read now
Read now
Marcin J. Mizianty, Zhenling Peng & Lukasz Kurgan. (2013) MFDp2. Intrinsically Disordered Proteins 1:1.
Read now
Read now
Articles from other publishers (124)
Zexi Yang, Yan Wang, Xinye Ni & Sen Yang. (2023) DeepDRP: Prediction of intrinsically disordered regions based on integrated view deep learning architecture from transformer-enhanced and protein information. International Journal of Biological Macromolecules 253, pages 127390.
Crossref
Crossref
Yi-Jun Tang, Ke Yan, Xingyi Zhang, Ye Tian & Bin Liu. (2023) Protein intrinsically disordered region prediction by combining neural architecture search and multi-objective genetic algorithm. BMC Biology 21:1.
Crossref
Crossref
Yidong Song, Qianmu Yuan, Sheng Chen, Ken Chen, Yaoqi Zhou & Yuedong Yang. (2023) Fast and accurate protein intrinsic disorder prediction by using a pretrained language model. Briefings in Bioinformatics 24:4.
Crossref
Crossref
Fuhao Zhang, Min Li, Jian Zhang, Wenbo Shi & Lukasz Kurgan. (2023) DeepPRObind: Modular Deep Learner that Accurately Predicts Structure and Disorder-Annotated Protein Binding Residues. Journal of Molecular Biology 435:14, pages 167945.
Crossref
Crossref
Vladimir N. Uversky & Lukasz Kurgan. (2023) Overview Update: Computational Prediction of Intrinsic Disorder in Proteins. Current Protocols 3:6.
Crossref
Crossref
Yihe Pang & Bin Liu. (2023) TransDFL: Identification of Disordered Flexible Linkers in Proteins by Transfer Learning. Genomics, Proteomics & Bioinformatics 21:2, pages 359-369.
Crossref
Crossref
Istvan Redl, Carlo Fisicaro, Oliver Dutton, Falk Hoffmann, Louie Henderson, Benjamin M J Owens, Matthew Heberling, Emanuele Paci & Kamil Tamiola. (2023) ADOPT: intrinsic protein disorder prediction through deep bidirectional transformers. NAR Genomics and Bioinformatics 5:2.
Crossref
Crossref
Bingqing Han, Chongjiao Ren, Wenda Wang, Jiashan Li & Xinqi Gong. (2023) Computational Prediction of Protein Intrinsically Disordered Region Related Interactions and Functions. Genes 14:2, pages 432.
Crossref
Crossref
Christos E. Kouros, Vasiliki Makri, Christos A. Ouzounis & Anastasia Chasapi. (2023) Disease association and comparative genomics of compositional bias in human proteins. F1000Research 12, pages 198.
Crossref
Crossref
Christos E. Kouros, Vasiliki Makri, Christos A. Ouzounis & Anastasia Chasapi. (2023) Disease association and comparative genomics of compositional bias in human proteins. F1000Research 12, pages 198.
Crossref
Crossref
Rajkumar Chakraborty & Yasha Hasija. (2022) Predicting protein intrinsically disordered regions by applying natural language processing practices. Soft Computing 26:22, pages 12343-12353.
Crossref
Crossref
Ranran Chen, Xinlu Li, Yaqing Yang, Xixi Song, Cheng Wang & Dongdong Qiao. (2022) Prediction of protein-protein interaction sites in intrinsically disordered proteins. Frontiers in Molecular Biosciences 9.
Crossref
Crossref
Die Chen, Hua Zhang, Zeqi Chen, Bo Xie & Ye Wang. (2022) Comparative Analysis on Alignment-Based and Pretrained Feature Representations for the Identification of DNA-Binding Proteins. Computational and Mathematical Methods in Medicine 2022, pages 1-14.
Crossref
Crossref
Gabriele Orlando, Daniele Raimondi, Francesco Codicè, Francesco Tabaro & Wim Vranken. (2022) Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics. Journal of Molecular Biology 434:12, pages 167579.
Crossref
Crossref
Xingming Zeng, Haiyuan Liu & Hao He. (2022) Prediction of Intrinsically Disordered Proteins Using Machine Learning Based on Low Complexity Methods. Algorithms 15:3, pages 86.
Crossref
Crossref
Jiaxiang Zhao & Zengke Wang. (2022) Identifying Intrinsically Disordered Protein Regions through a Deep Neural Network with Three Novel Sequence Features. Life 12:3, pages 345.
Crossref
Crossref
Yi-Jun Tang, Yi-He Pang & Bin Liu. (2022) DeepIDP-2L: protein intrinsically disordered region prediction by combining convolutional attention network and hierarchical attention network. Bioinformatics 38:5, pages 1252-1260.
Crossref
Crossref
Hao He & Yong Yang. (2021) Computational Prediction of Intrinsically Disordered Proteins Based on Protein Sequences and Convolutional Neural Networks. Computational Intelligence and Neuroscience 2021, pages 1-8.
Crossref
Crossref
Qi Cheng, Bo He, Chengkui Zhao, Hongyuan Bi, Duojiao Chen, Shuangze Han, Haikuan Gao & Weixing Feng. (2021) Prediction of functional microexons by transfer learning. BMC Genomics 22:1.
Crossref
Crossref
Chia-Tzu Ho, Yu-Wei Huang, Teng-Ruei Chen, Chia-Hua Lo & Wei-Cheng Lo. (2021) Discovering the Ultimate Limits of Protein Secondary Structure Prediction. Biomolecules 11:11, pages 1627.
Crossref
Crossref
Hang Wei, Qing Liao & Bin Liu. (2021) iLncRNAdis-FB: Identify lncRNA-Disease Associations by Fusing Biological Feature Blocks Through Deep Neural Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics 18:5, pages 1946-1957.
Crossref
Crossref
Hao He & Yong Yang. (2021) Prediction of Intrinsically Disordered Proteins with Convolutional Neural Networks based on Feature Selection. Prediction of Intrinsically Disordered Proteins with Convolutional Neural Networks based on Feature Selection.
Teng-Ruei Chen, Sheng-Hung Juan, Yu-Wei Huang, Yen-Cheng Lin & Wei-Cheng Lo. (2021) A secondary structure-based position-specific scoring matrix applied to the improvement in protein secondary structure prediction. PLOS ONE 16:7, pages e0255076.
Crossref
Crossref
Bing-Liang Fan, Zheng Jiang, Jun Sun & Rong Liu. (2021) Systematic characterization and prediction of coenzyme A-associated proteins using sequence and network information. Briefings in Bioinformatics 22:4.
Crossref
Crossref
Shrinath Iyer. (2021) Identify protein disorder from amino acid sequences with Machine learning. Identify protein disorder from amino acid sequences with Machine learning.
Avdesh Mishra, Md Wasi Ul Kabir & Md Tamjidul Hoque. (2021) diSBPred: A machine learning based approach for disulfide bond prediction. Computational Biology and Chemistry 91, pages 107436.
Crossref
Crossref
Pengchang Xu, Jiaxiang Zhao & Jie Zhang. (2021) Identification of Intrinsically Disordered Protein Regions Based on Deep Neural Network-VGG16. Algorithms 14:4, pages 107.
Crossref
Crossref
Yumeng Liu, Xiaolong Wang & Bin Liu. (2021) RFPR-IDP: reduce the false positive rates for intrinsically disordered protein and region prediction by incorporating both fully ordered proteins and disordered proteins. Briefings in Bioinformatics 22:2, pages 2000-2011.
Crossref
Crossref
Yi-Jun Tang, Yi-He Pang & Bin Liu. (2020) IDP-Seq2Seq: identification of intrinsically disordered regions based on sequence to sequence learning. Bioinformatics 36:21, pages 5177-5186.
Crossref
Crossref
Lukasz Kurgan, Min Li & Yaohang Li. 2021. Systems Medicine. Systems Medicine
159
169
.
Akila Katuwawala, Christopher J Oldfield & Lukasz Kurgan. (2020) Accuracy of protein-level disorder predictions. Briefings in Bioinformatics 21:5, pages 1509-1522.
Crossref
Crossref
Jack HansonKuldip K. PaliwalThomas LitfinYuedong YangYaoqi Zhou. (2020) Getting to Know Your Neighbor: Protein Structure Prediction Comes of Age with Contextual Machine Learning. Journal of Computational Biology 27:5, pages 796-814.
Crossref
Crossref
Zhicheng LiShijian LiXian WeiXubiao PengQing Zhao. (2020) Recovering the Missing Regions in Crystal Structures from the Nuclear Magnetic Resonance Measurement Data Using Matrix Completion Method. Journal of Computational Biology 27:5, pages 709-717.
Crossref
Crossref
Katarzyna Sołtys & Andrzej Ożyhar. (2020) Ordered structure-forming properties of the intrinsically disordered AB region of hRXRγ and its ability to promote liquid-liquid phase separation. The Journal of Steroid Biochemistry and Molecular Biology 198, pages 105571.
Crossref
Crossref
WeiXia Xie & Yong E. Feng. (2020) Prediction of the Disordered Regions of Intrinsically Disordered Proteins Based on the Molecular Functions. Protein & Peptide Letters 27:4, pages 279-286.
Crossref
Crossref
Hiroto Anbo, Hiroki Amagai & Satoshi Fukuchi. (2020) NeProc predicts binding segments in intrinsically disordered regions without learning binding region sequences. Biophysics and Physicobiology 17:0, pages 147-154.
Crossref
Crossref
Tareq Hameduh, Yazan Haddad, Vojtech Adam & Zbynek Heger. (2020) Homology modeling in the time of collective and artificial intelligence. Computational and Structural Biotechnology Journal 18, pages 3494-3506.
Crossref
Crossref
Zhonghua Wu, Gang Hu, Christopher J. Oldfield & Lukasz Kurgan. 2020. Protein Structure Prediction. Protein Structure Prediction
83
101
.
Christopher J. Oldfield, Xiao Fan, Chen Wang, A. Keith Dunker & Lukasz Kurgan. 2020. Intrinsically Disordered Proteins. Intrinsically Disordered Proteins
21
35
.
Akila Katuwawala, Christopher J. Oldfield & Lukasz Kurgan. (2019) DISOselect: Disorder predictor selection at the protein level. Protein Science 29:1, pages 184-200.
Crossref
Crossref
Hai Lin, Katherine A. Hargreaves, Rudong Li, Jill L. Reiter, Yue Wang, Matthew Mort, David N. Cooper, Yaoqi Zhou, Chi Zhang, Michael T. Eadon, M. Eileen Dolan, Joseph Ipe, Todd C. Skaar & Yunlong Liu. (2019) RegSNPs-intron: a computational framework for predicting pathogenic impact of intronic single nucleotide variants. Genome Biology 20:1.
Crossref
Crossref
Jack Hanson, Kuldip K. Paliwal, Thomas Litfin & Yaoqi Zhou. (2019) SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning. Genomics, Proteomics & Bioinformatics 17:6, pages 645-656.
Crossref
Crossref
Yumeng Liu, Shengyu Chen, Xiaolong Wang & Bin Liu. (2019) Identification of Intrinsically Disordered Proteins and Regions by Length-Dependent Predictors Based on Conditional Random Fields. Molecular Therapy - Nucleic Acids 17, pages 396-404.
Crossref
Crossref
Eshel Faraggi, A. Keith Dunker, Robert L. Jernigan & Andrzej Kloczkowski. (2019) Entropy, Fluctuations, and Disordered Proteins. Entropy 21:8, pages 764.
Crossref
Crossref
Mak B. Djulbegovic & Vladimir N. Uversky. (2019) Ferroptosis – An iron- and disorder-dependent programmed cell death. International Journal of Biological Macromolecules 135, pages 1052-1069.
Crossref
Crossref
Hao He, Jiaxiang Zhao & Guiling Sun. (2019) The Prediction of Intrinsically Disordered Proteins Based on Feature Selection. Algorithms 12:2, pages 46.
Crossref
Crossref
Alexander D. Dergunov, Eugeny V. Savushkin, Liudmila V. Dergunova & Dmitry Y. Litvinov. (2018) Significance of Cholesterol-Binding Motifs in ABCA1, ABCG1, and SR-B1 Structure. The Journal of Membrane Biology 252:1, pages 41-60.
Crossref
Crossref
Yumeng Liu, Xiaolong Wang & Bin Liu. (2019) A comprehensive review and comparison of existing computational methods for intrinsically disordered protein and region prediction. Briefings in Bioinformatics 20:1, pages 330-346.
Crossref
Crossref
Alok Arun, Susana M Coelho, Akira F Peters, Simon Bourdareau, Laurent Pérès, Delphine Scornet, Martina Strittmatter, Agnieszka P Lipinska, Haiqin Yao, Olivier Godfroy, Gabriel J Montecinos, Komlan Avia, Nicolas Macaisne, Christelle Troadec, Abdelhafid Bendahmane & J Mark Cock. (2019) Convergent recruitment of TALE homeodomain life cycle regulators to direct sporophyte development in land plants and brown algae. eLife 8.
Crossref
Crossref
Akila Katuwawala, Zhenling Peng, Jianyi Yang & Lukasz Kurgan. (2019) Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions. Computational and Structural Biotechnology Journal 17, pages 454-462.
Crossref
Crossref
Orkid Coskuner & Vladimir N. Uversky. 2019. Dancing protein clouds: Intrinsically disordered proteins in health and disease, Part A. Dancing protein clouds: Intrinsically disordered proteins in health and disease, Part A
145
223
.
Christopher J. Oldfield, Vladimir N. Uversky, A. Keith Dunker & Lukasz Kurgan. 2019. Intrinsically Disordered Proteins. Intrinsically Disordered Proteins
1
34
.
Bálint Mészáros, Zsuzsanna Dosztányi, Erzsébet Fichó, Csaba Magyar & István Simon. 2019. Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes. Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes
561
596
.
Jianzhao Gao, Yuedong Yang & Yaoqi Zhou. (2018) Grid-based prediction of torsion angle probabilities of protein backbone and its application to discrimination of protein intrinsic disorder regions and selection of model structures. BMC Bioinformatics 19:1.
Crossref
Crossref
Jack Hanson, Kuldip Paliwal & Yaoqi Zhou. (2018) Accurate Single-Sequence Prediction of Protein Intrinsic Disorder by an Ensemble of Deep Recurrent and Convolutional Architectures. Journal of Chemical Information and Modeling 58:11, pages 2369-2376.
Crossref
Crossref
Fanchi Meng & Lukasz Kurgan. (2018) High‐throughput prediction of disordered moonlighting regions in protein sequences. Proteins: Structure, Function, and Bioinformatics 86:10, pages 1097-1110.
Crossref
Crossref
Yumeng Liu, Xiaolong Wang & Bin Liu. (2018) IDP–CRF: Intrinsically Disordered Protein/Region Identification Based on Conditional Random Fields. International Journal of Molecular Sciences 19:9, pages 2483.
Crossref
Crossref
Denson Smith, Sumanth Yenduri, Sumaiya Iqbal & P. Venkata Krishna. (2018) An efficient distributed protein disorder prediction with pasted samples. Computers & Electrical Engineering 65, pages 342-356.
Crossref
Crossref
Yaser Fattahian, Ali Riahi-Madvar, Reza Mirzaee, Gholamreza Asadikaram & Mohammad Reza Rahbar. (2017) In silico locating the immune-reactive segments of Lepidium draba peroxidase and designing a less immune-reactive enzyme derivative. Computational Biology and Chemistry 70, pages 21-30.
Crossref
Crossref
Mark Livingstone, Lukas Folkman, Yuedong Yang, Ping Zhang, Matthew Mort, David N. Cooper, Yunlong Liu, Bela Stantic & Yaoqi Zhou. (2017) Investigating DNA-, RNA-, and protein-based features as a means to discriminate pathogenic synonymous variants. Human Mutation 38:10, pages 1336-1347.
Crossref
Crossref
Xinjun Zhang, Meng Li, Hai Lin, Xi Rao, Weixing Feng, Yuedong Yang, Matthew Mort, David N. Cooper, Yue Wang, Yadong Wang, Clark Wells, Yaoqi Zhou & Yunlong Liu. (2017) regSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution. Human Genetics 136:9, pages 1279-1289.
Crossref
Crossref
Fanchi Meng, Vladimir N. Uversky & Lukasz Kurgan. (2017) Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions. Cellular and Molecular Life Sciences 74:17, pages 3069-3090.
Crossref
Crossref
Marie-Pierre Dubrana, Julia Guéguéniat, Clothilde Bertin, Sybille Duret, Nathalie Arricau-Bouvery, Stéphane Claverol, Carole Lartigue, Alain Blanchard, Joël Renaudin & Laure Béven. (2017) Proteolytic Post-Translational Processing of Adhesins in a Pathogenic Bacterium. Journal of Molecular Biology 429:12, pages 1889-1902.
Crossref
Crossref
Jack Hanson, Yuedong Yang, Kuldip Paliwal & Yaoqi Zhou. (2017) Improving protein disorder prediction by deep bidirectional long short-term memory recurrent neural networks. Bioinformatics 33:5, pages 685-692.
Crossref
Crossref
Tuo Zhang, Eshel Faraggi, Zhixiu Li & Yaoqi Zhou. 2017. Prediction of Protein Secondary Structure. Prediction of Protein Secondary Structure
159
174
.
Meng Li, Weixing Feng, Xinjun Zhang, Yuedong Yang, Kejun Wang, Matthew Mort, David N Cooper, Yue Wang, Yaoqi Zhou & Yunlong Liu. (2017) ExonImpact: Prioritizing Pathogenic Alternative Splicing Events. Human Mutation 38:1, pages 16-24.
Crossref
Crossref
Ghazaleh Taherzadeh, Yaoqi Zhou, Alan Wee-Chung Liew & Yuedong Yang. (2016) Sequence-Based Prediction of Protein–Carbohydrate Binding Sites Using Support Vector Machines. Journal of Chemical Information and Modeling 56:10, pages 2115-2122.
Crossref
Crossref
Weiwei Zhang, Mingming Yang, Yuedong Yang, Jian Zhan, Yaoqi Zhou & Xin Zhao. (2016) Optimal secretion of alkali-tolerant xylanase in Bacillus subtilis by signal peptide screening. Applied Microbiology and Biotechnology 100:20, pages 8745-8756.
Crossref
Crossref
Sandra Postel, Daniel Deredge, Daniel A Bonsor, Xiong Yu, Kay Diederichs, Saskia Helmsing, Aviv Vromen, Assaf Friedler, Michael Hust, Edward H Egelman, Dorothy Beckett, Patrick L Wintrode & Eric J Sundberg. (2016) Bacterial flagellar capping proteins adopt diverse oligomeric states. eLife 5.
Crossref
Crossref
Sumaiya Iqbal & Md Tamjidul Hoque. (2016) Estimation of Position Specific Energy as a Feature of Protein Residues from Sequence Alone for Structural Classification. PLOS ONE 11:9, pages e0161452.
Crossref
Crossref
João Paulo Machado, Siby Philip, Emanuel Maldonado, Stephen J. O’Brien, Warren E. Johnson & Agostinho Antunes. (2016) Positive Selection Linked with Generation of Novel Mammalian Dentition Patterns. Genome Biology and Evolution 8:9, pages 2748-2759.
Crossref
Crossref
Sheng Wang, Jianzhu Ma & Jinbo Xu. (2016) AUCpreD: proteome-level protein disorder prediction by AUC-maximized deep convolutional neural fields. Bioinformatics 32:17, pages i672-i679.
Crossref
Crossref
D. Craig Ayre, Nikitha K. Pallegar, Nicholas A. Fairbridge, Marta Canuti, Andrew S. Lang & Sherri L. Christian. (2016) Analysis of the structure, evolution, and expression of CD24, an important regulator of cell fate. Gene 590:2, pages 324-337.
Crossref
Crossref
Shelly DeForte & Vladimir Uversky. (2016) Order, Disorder, and Everything in Between. Molecules 21:8, pages 1090.
Crossref
Crossref
Jia-Feng Yu, Zanxia Cao, Yuedong Yang, Chun-Ling Wang, Zhen-Dong Su, Ya-Wei Zhao, Ji-Hua Wang & Yaoqi Zhou. (2016) Natural protein sequences are more intrinsically disordered than random sequences. Cellular and Molecular Life Sciences 73:15, pages 2949-2957.
Crossref
Crossref
Eva König, Johannes Rainer & Francisco S. Domingues. (2016) Computational assessment of feature combinations for pathogenic variant prediction. Molecular Genetics & Genomic Medicine 4:4, pages 431-446.
Crossref
Crossref
Sandeep Kumar Narasimha Mulukala, Rajkishor Nishad, Lakshmi Prasanna Kolligundla, Moin A. Saleem, Nagu Prakash Prabhu & Anil Kumar Pasupulati. (2016)
In silico
Structural characterization of podocin and assessment of nephrotic syndrome-associated podocin mutants
. IUBMB Life 68:7, pages 578-588.
Crossref
Crossref
Aaron P Ragsdale, Alec J Coffman, PingHsun Hsieh, Travis J Struck & Ryan N Gutenkunst. (2016) Triallelic Population Genomics for Inferring Correlated Fitness Effects of Same Site Nonsynonymous Mutations. Genetics 203:1, pages 513-523.
Crossref
Crossref
Joanna Lange, Lucjan S. Wyrwicz & Gert Vriend. (2016) KMAD: knowledge-based multiple sequence alignment for intrinsically disordered proteins. Bioinformatics 32:6, pages 932-936.
Crossref
Crossref
Lukas Folkman, Bela Stantic, Abdul Sattar & Yaoqi Zhou. (2016) EASE-MM: Sequence-Based Prediction of Mutation-Induced Stability Changes with Feature-Based Multiple Models. Journal of Molecular Biology 428:6, pages 1394-1405.
Crossref
Crossref
Ashish Runthala & Shibasish Chowdhury. 2016. Hybrid Soft Computing Approaches. Hybrid Soft Computing Approaches
75
105
.
Philippe Lieutaud, François Ferron & Sonia Longhi. 2016. Data Mining Techniques for the Life Sciences. Data Mining Techniques for the Life Sciences
265
299
.
Gábor E. Tusnády, László Dobson & Peter Tompa. (2015) Disordered regions in transmembrane proteins. Biochimica et Biophysica Acta (BBA) - Biomembranes 1848:11, pages 2839-2848.
Crossref
Crossref
Nawar Malhis, Eric T. C. Wong, Roy Nassar & Jörg Gsponer. (2015) Computational Identification of MoRFs in Protein Sequences Using Hierarchical Application of Bayes Rule. PLOS ONE 10:10, pages e0141603.
Crossref
Crossref
Sumaiya Iqbal & Md Tamjidul Hoque. (2015) DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel. PLOS ONE 10:10, pages e0141551.
Crossref
Crossref
Jianzong Li, Yu Feng, Xiaoyun Wang, Jing Li, Wen Liu, Li Rong & Jinku Bao. (2015) An Overview of Predictors for Intrinsically Disordered Proteins over 2010–2014. International Journal of Molecular Sciences 16:10, pages 23446-23462.
Crossref
Crossref
Antje Aufderheide, Pia Unverdorben, Wolfgang Baumeister & Friedrich Förster. (2015) Structural disorder and its role in proteasomal degradation. FEBS Letters 589:19PartA, pages 2552-2560.
Crossref
Crossref
Jennifer Atkins, Samuel Boateng, Thomas Sorensen & Liam McGuffin. (2015) Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental Studies. International Journal of Molecular Sciences 16:8, pages 19040-19054.
Crossref
Crossref
Sheng Wang, Shunyan Weng, Jianzhu Ma & Qingming Tang. (2015) DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields. International Journal of Molecular Sciences 16:8, pages 17315-17330.
Crossref
Crossref
Xin Deng, Jordan Gumm, Suman Karki, Jesse Eickholt & Jianlin Cheng. (2015) An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions. International Journal of Molecular Sciences 16:12, pages 15384-15404.
Crossref
Crossref
Zhiheng Wang, Qianqian Yang, Tonghua Li & Peisheng Cong. (2015) DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach. PLOS ONE 10:6, pages e0128334.
Crossref
Crossref
Lukas Folkman, Yuedong Yang, Zhixiu Li, Bela Stantic, Abdul Sattar, Matthew Mort, David N. Cooper, Yunlong Liu & Yaoqi Zhou. (2015) DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations employing sequence and structural properties at nucleotide and protein levels. Bioinformatics 31:10, pages 1599-1606.
Crossref
Crossref
Siddharth Pandya, Travis J. Struck, Brian K. Mannakee, Mary Paniscus & Ryan N. Gutenkunst. (2015) Testing whether Metazoan Tyrosine Loss Was Driven by Selection against Promiscuous Phosphorylation. Molecular Biology and Evolution 32:1, pages 144-152.
Crossref
Crossref
L. Michel Espinoza-Fonseca & Ameeta Kelekar. (2015) High-resolution structural characterization of Noxa, an intrinsically disordered protein, by microsecond molecular dynamics simulations. Molecular BioSystems 11:7, pages 1850-1856.
Crossref
Crossref
Eshel Faraggi & Andrzej Kloczkowski. 2015. Artificial Neural Networks. Artificial Neural Networks
165
178
.
Fei Huang, Christopher J Oldfield, Bin Xue, Wei-Lun Hsu, Jingwei Meng, Xiaowen Liu, Li Shen, Pedro Romero, Vladimir N Uversky & A Keith Dunker. (2014) Improving protein order-disorder classification using charge-hydropathy plots. BMC Bioinformatics 15:S17.
Crossref
Crossref
Carlos Bermejo-Das-Neves, Hoan-Ngoc Nguyen, Olivier Poch & Julie D Thompson. (2014) A comprehensive study of small non-frameshift insertions/deletions in proteins and prediction of their phenotypic effects by a machine learning method (KD4i). BMC Bioinformatics 15:1.
Crossref
Crossref
Sumaiya Iqbal, Md Nasrul Islam & Md Tamjidul Hoque. (2014) Improved protein disorder predictor by smoothing output. Improved protein disorder predictor by smoothing output.
Alexander D. Dergunov. (2014) Prediction of the influences of missense mutations on cholesteryl ester transfer protein structure. Archives of Biochemistry and Biophysics 564, pages 67-73.
Crossref
Crossref
Hua Zhang & Lukasz Kurgan. (2014) Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models. Amino Acids 46:12, pages 2665-2680.
Crossref
Crossref
Wei Deng, Sungyun Cho, Pin-Chuan Su, Bryan W. Berger & Renhao Li. (2014) Membrane-enabled dimerization of the intrinsically disordered cytoplasmic domain of ADAM10. Proceedings of the National Academy of Sciences 111:45, pages 15987-15992.
Crossref
Crossref
William M. Holmes, Brian K. Mannakee, Ryan N. Gutenkunst & Tricia R. Serio. (2014) Loss of amino-terminal acetylation suppresses a prion phenotype by modulating global protein folding. Nature Communications 5:1.
Crossref
Crossref
Heidi Ali, Siddhaling Urolagin, Ömer Gurarslan & Mauno Vihinen. (2014) Performance of Protein Disorder Prediction Programs on Amino Acid Substitutions. Human Mutation 35:7, pages 794-804.
Crossref
Crossref
Qianli Huang, Jinhui Chang, Man Kit Cheung, Wenyan Nong, Lei Li, Ming-tsung Lee & Hoi Shan Kwan. (2014) Human Proteins with Target Sites of Multiple Post-Translational Modification Types Are More Prone to Be Involved in Disease. Journal of Proteome Research 13:6, pages 2735-2748.
Crossref
Crossref
X. Zhang, H. Lin, H. Zhao, Y. Hao, M. Mort, D. N. Cooper, Y. Zhou & Y. Liu. (2014) Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation. Human Molecular Genetics 23:11, pages 3024-3034.
Crossref
Crossref
Lukas Folkman, Bela Stantic & Abdul Sattar. (2014) Feature-based multiple models improve classification of mutation-induced stability changes. BMC Genomics 15:S4.
Crossref
Crossref
Edward E. PryorJr.Jr. & Michael C. Wiener. (2014) A Critical Evaluation of in silico Methods for Detection of Membrane Protein Intrinsic Disorder. Biophysical Journal 106:8, pages 1638-1649.
Crossref
Crossref
Ashraf Yaseen & Yaohang Li. (2014) Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy. Journal of Chemical Information and Modeling 54:3, pages 992-1002.
Crossref
Crossref
Maja Milanovic, Michael Kracht & M. Lienhard Schmitz. (2014) The cytokine-induced conformational switch of nuclear factor κB p65 is mediated by p65 phosphorylation. Biochemical Journal 457:3, pages 401-413.
Crossref
Crossref
Wangchao Lou, Xiaoqing Wang, Fan Chen, Yixiao Chen, Bo Jiang & Hua Zhang. (2014) Sequence Based Prediction of DNA-Binding Proteins Based on Hybrid Feature Selection Using Random Forest and Gaussian Naïve Bayes. PLoS ONE 9:1, pages e86703.
Crossref
Crossref
Zhenling Peng, Marcin J. Mizianty & Lukasz Kurgan. (2014) Genome-scale prediction of proteins with long intrinsically disordered regions. Proteins: Structure, Function, and Bioinformatics 82:1, pages 145-158.
Crossref
Crossref
Julien Becker, Francis Maes & Louis Wehenkel. (2013) On the Encoding of Proteins for Disordered Regions Prediction. PLoS ONE 8:12, pages e82252.
Crossref
Crossref
Jihua Wang, Yuedong Yang, Zanxia Cao, Zhixiu Li, Huiying Zhao & Yaoqi Zhou. (2013) The Role of Semidisorder in Temperature Adaptation of Bacterial FlgM Proteins. Biophysical Journal 105:11, pages 2598-2605.
Crossref
Crossref
Tuo Zhang, Eshel Faraggi, Zhixiu Li & Yaoqi Zhou. (2013) Intrinsically Semi-disordered State and Its Role in Induced Folding and Protein Aggregation. Cell Biochemistry and Biophysics 67:3, pages 1193-1205.
Crossref
Crossref
Alexander D. Dergunov. (2013) Mutation mapping of apolipoprotein A-I structure assisted with the putative cholesterol recognition regions. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 1834:10, pages 2030-2035.
Crossref
Crossref
Jing Yan, Marcin J. Mizianty, Paul L. Filipow, Vladimir N. Uversky & Lukasz Kurgan. (2013) RAPID: Fast and accurate sequence-based prediction of intrinsic disorder content on proteomic scale. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics 1834:8, pages 1671-1680.
Crossref
Crossref
Thomas J. McCorvie, Tyler J. Gleason, Judith L. Fridovich-Keil & David J. Timson. (2013) Misfolding of galactose 1-phosphate uridylyltransferase can result in type I galactosemia. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1832:8, pages 1279-1293.
Crossref
Crossref
Qiong Wei & Roland L. Dunbrack. (2013) The Role of Balanced Training and Testing Data Sets for Binary Classifiers in Bioinformatics. PLoS ONE 8:7, pages e67863.
Crossref
Crossref
Zhixiu LiYuedong YangJian ZhanLiang DaiYaoqi Zhou. (2013) Energy Functions in De Novo Protein Design: Current Challenges and Future Prospects. Annual Review of Biophysics 42:1, pages 315-335.
Crossref
Crossref
Xiao-yan Zhang, Long-jian Lu, Qi Song, Qian-qian Yang, Da-peng Li, Jiang-ming Sun, Tong-hua Li & Pei-sheng Cong. (2013) DomHR: Accurately Identifying Domain Boundaries in Proteins Using a Hinge Region Strategy. PLoS ONE 8:4, pages e60559.
Crossref
Crossref
Jianlin Cheng, Jilong Li, Zheng Wang, Jesse Eickholt & Xin Deng. (2012) The MULTICOM toolbox for protein structure prediction. BMC Bioinformatics 13:1.
Crossref
Crossref
Lionel Tarrago, Alaattin Kaya, Eranthie Weerapana, Stefano M. Marino & Vadim N. Gladyshev. (2012) Methionine Sulfoxide Reductases Preferentially Reduce Unfolded Oxidized Proteins and Protect Cells from Oxidative Protein Unfolding. Journal of Biological Chemistry 287:29, pages 24448-24459.
Crossref
Crossref
Fatemeh Miri Disfani, Wei-Lun Hsu, Marcin J. Mizianty, Christopher J. Oldfield, Bin Xue, A. Keith Dunker, Vladimir N. Uversky & Lukasz Kurgan. (2012) MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins. Bioinformatics 28:12, pages i75-i83.
Crossref
Crossref
Vitali Sikirzhytski, Natalya I. Topilina, Gaius A. Takor, Seiichiro Higashiya, John T. Welch, Vladimir N. Uversky & Igor K. Lednev. (2012) Fibrillation Mechanism of a Model Intrinsically Disordered Protein Revealed by 2D Correlation Deep UV Resonance Raman Spectroscopy. Biomacromolecules 13:5, pages 1503-1509.
Crossref
Crossref