Li et al., 2020 - Google Patents
Remarks on computational method for identifying acid and alkaline enzymesLi et al., 2020
- Document ID
- 3162974324909551144
- Author
- Li H
- Du H
- Wang X
- Gao P
- Liu Y
- Lin W
- Publication year
- Publication venue
- Current Pharmaceutical Design
External Links
Snippet
The catalytic efficiency of the enzyme is thousands of times higher than that of ordinary catalysts. Thus, they are widely used in industrial and medical fields. However, enzymes with protein structure can be destroyed and inactivated in high temperature, over acid or …
- 102000004190 Enzymes 0 title abstract description 109
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/20—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/16—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for molecular structure, e.g. structure alignment, structural or functional relations, protein folding, domain topologies, drug targeting using structure data, involving two-dimensional or three-dimensional structures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
- G06F19/14—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for phylogeny or evolution, e.g. evolutionarily conserved regions determination or phylogenetic tree construction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/70—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds
- G06F19/706—Chemoinformatics, i.e. data processing methods or systems for the retrieval, analysis, visualisation, or storage of physicochemical or structural data of chemical compounds for drug design with the emphasis on a therapeutic agent, e.g. ligand-biological target interactions, pharmacophore generation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30587—Details of specialised database models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for programme control, e.g. control unit
- G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zheng et al. | Folding non-homologous proteins by coupling deep-learning contact maps with I-TASSER assembly simulations | |
| Tang et al. | Machine learning on protein–protein interaction prediction: models, challenges and trends | |
| Zhang et al. | iBLP: An XGBoost‐based predictor for identifying bioluminescent proteins | |
| Camargo et al. | RNAsamba: neural network-based assessment of the protein-coding potential of RNA sequences | |
| Liu et al. | iEnhancer-EL: identifying enhancers and their strength with ensemble learning approach | |
| Yang et al. | iRNA-2OM: a sequence-based predictor for identifying 2′-O-methylation sites in Homo sapiens | |
| Ru et al. | Incorporating distance-based top-n-gram and random forest to identify electron transport proteins | |
| Tang et al. | Prediction of cell-penetrating peptides with feature selection techniques | |
| Zhang et al. | Using the concept of Chou’s pseudo amino acid composition to predict protein subcellular localization: an approach by incorporating evolutionary information and von Neumann entropies | |
| Butt et al. | CanLect-Pred: A cancer therapeutics tool for prediction of target cancerlectins using experiential annotated proteomic sequences | |
| Ding et al. | Laplacian Regularized Sparse Representation Based Classifier for Identifying DNA N4-Methylcytosine Sites via $ L_ {2, 1/2} $ L 2, 1/2-Matrix Norm | |
| Zeng et al. | An empirical study of features fusion techniques for protein-protein interaction prediction | |
| Al-Barakati et al. | RF-GlutarySite: a random forest based predictor for glutarylation sites | |
| Hasan et al. | Protein subcellular localization prediction using multiple kernel learning based support vector machine | |
| Qian et al. | Multi-view kernel sparse representation for identification of membrane protein types | |
| Wang et al. | An ensemble approach for large-scale identification of protein-protein interactions using the alignments of multiple sequences | |
| Pugalenthi et al. | Nglyc: a random forest method for prediction of N-glycosylation sites in eukaryotic protein sequence | |
| Li et al. | iPhoPred: a predictor for identifying phosphorylation sites in human protein | |
| Kabir et al. | Large-scale comparative review and assessment of computational methods for phage virion proteins identification | |
| Hu et al. | TargetDBP+: enhancing the performance of identifying DNA-binding proteins via weighted convolutional features | |
| Meher et al. | ir-HSP: improved recognition of heat shock proteins, their families and sub-types based on g-spaced di-peptide features and support vector machine | |
| Jia et al. | KK-DBP: a multi-feature fusion method for DNA-binding protein identification based on random forest | |
| Dou et al. | iRNA-m5C_NB: a novel predictor to identify RNA 5-Methylcytosine sites based on the Naive Bayes classifier | |
| Huang et al. | 6mA-Pred: identifying DNA N6-methyladenine sites based on deep learning | |
| Li et al. | Remarks on computational method for identifying acid and alkaline enzymes |