[1]
|
Tlcrys: Transfer learning based method for protein crystallization prediction
|
|
International Journal of Molecular …,
2022 |
|
|
[2]
|
ATTCry: Attention-based neural network model for protein crystallization prediction
|
|
Neurocomputing,
2021 |
|
|
[3]
|
XRRpred: accurate predictor of crystal structure quality from protein sequence
|
|
Bioinformatics,
2021 |
|
|
[4]
|
Machine Learning Approaches to Predict Protein Crystallization Propensities
|
|
2020 |
|
|
[5]
|
CLPred: a sequence-based protein crystallization predictor using BLSTM neural network
|
|
2020 |
|
|
[6]
|
DHS-Crystallize: Deep-Hybrid-Sequence based method for predicting protein Crystallization
|
|
2020 |
|
|
[7]
|
CLPred: A sequence-based protein crystallization pre-dictor using BLSTM neural network
|
|
2020 |
|
|
[8]
|
Correlation of Combined Characters of Amino Acid and Whole Protein with Success Rate of Crystallization of Lactobacillus Proteins
|
|
2019 |
|
|
[9]
|
BCrystal: An Interpretable Sequence-Based Protein Crystallization Predictor
|
|
2019 |
|
|
[10]
|
Correlating Combined Features of Amino Acid and Protein with Crystallization Propensity of Proteins from Mycobacterium tuberculosis
|
|
2019 |
|
|
[11]
|
Prediction of Crystallization Propensity of Proteins from Bacillus haloduran Using Various Amino Acid and Protein Features
|
|
2019 |
|
|
[12]
|
DeepCrystal: a deep learning framework for sequence-based protein crystallization prediction
|
|
2018 |
|
|
[13]
|
Identification and characterization of sodium and chloride-dependent gamma-aminobutyric acid (GABA) transporters from eukaryotic pathogens as a potential …
|
|
Bioinformation,
2018 |
|
|
[14]
|
Taxonomic Landscape of the Dark Proteomes: Whole‐Proteome Scale Interplay Between Structural Darkness, Intrinsic Disorder, and Crystallization Propensity
|
|
Proteomics,
2018 |
|
|
[15]
|
Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity
|
|
Briefings in Bioinformatics,
2017 |
|
|
[16]
|
fDETECT webserver: fast predictor of propensity for protein production, purification, and crystallization
|
|
2017 |
|
|
[17]
|
Caracterización molecular de los factores involucrados en la regulación de la biosíntesis de ácidos micólicos en Mycobacterium tuberculosis
|
|
2017 |
|
|
[18]
|
Purification Propensity for Proteins from Bacillus halodurans. Enz Eng 5: 151. doi: 10.4172/2329-6674.1000151 Page 2 of 6 Volume 5• Issue 3• 1000151 Enz …
|
|
2016 |
|
|
[19]
|
Purification Propensity for Proteins from Bacillus halodurans. Enz Eng 5: 151. doi: 10.4172/2329-6674.1000151 Page 2 of 6 Volume 5• Issue 3• 1000151 …
|
|
2016 |
|
|
[20]
|
Cribado de las condiciones de cristalización de la Ubiquitina in silico y en el laboratorio
|
|
2016 |
|
|
[21]
|
Purification Propensity for Proteins from Bacillus halodurans. Enz Eng 5: 151. doi: 10.4172/2329-6674.1000151 Page 2 of 6 Volume 5• Issue 3• 1000151 Enz …
|
|
2016 |
|
|
[22]
|
Predicting Crystallization Propensity of Proteins from Arabidopsis Thaliana
|
|
Biological procedures online,
2015 |
|
|
[23]
|
Statistical Analysis of Crystallization Database Links Protein Physico-Chemical Features with Crystallization Mechanisms
|
|
PloS one,
2014 |
|
|
[24]
|
Protein Crystallization: Soft Matter and Chemical Physics Perspectives
|
|
2014 |
|
|
[25]
|
Statistical analysis of crystallization database links protein physicochemical features with crystallization mechanisms
|
|
arXiv preprint arXiv,
2013 |
|
|
[26]
|
Association of combined features of amino acid and protein withcrystallization propensity of proteins from Cytophaga Hutchinsoni
|
|
Zeitschrift für Kristallographie-Crystalline Materials,
2013 |
|
|
[27]
|
氨基酸和蛋白质的组合特征与秀丽隐杆线虫蛋白质的结晶倾向的相关分析
|
|
广西科学,
2013 |
|
|
[28]
|
Computational support systems for prediction and characterization of protein crystallization outcomes
|
|
2013 |
|
|
[29]
|
CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristic
|
|
Protein and peptide letters,
2012 |
|
|
[30]
|
Correlating dynamic amino acid properties with success rate of crystallization of proteins from Bacteroides vulgatus
|
|
Crystal Research and Technology,
2012 |
|
|
[31]
|
Predicting protein crystallizability and nucleation
|
|
Protein and peptide letters ,
2012 |
|
|
[32]
|
Sequence-based prediction of protein crystallization, purification and production propensity
|
|
Bioinformatics,
2011 |
|
|
[33]
|
ifc2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
|
|
Amino acids,
2011 |
|
|
[34]
|
Structural protein descriptors in 1-dimension and their sequence-based predictions
|
|
Current Protein and Peptide Science,
2011 |
|
|
[35]
|
iFC 2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
|
|
2011 |
|
|
[36]
|
Meta prediction of protein crystallization propensity
|
|
Biochemical and biophysical research communications ,
2009 |
|
|
[37]
|
De Novo Crystallization Condition Prediction with Deep Learning
|
|
Verge, M Mok, S Kang
|
|
|