Guo et al., 2022 - Google Patents
Context-aware poly (a) signal prediction model via deep spatial–temporal neural networksGuo et al., 2022
- Document ID
- 9627921964220345447
- Author
- Guo Y
- Zhou D
- Li P
- Li C
- Cao J
- Publication year
- Publication venue
- IEEE Transactions on Neural Networks and Learning Systems
External Links
Snippet
Polyadenylation [Poly (A)] is an essential process during messenger RNA (mRNA) maturation in biological eukaryote systems. Identifying Poly (A) signals (PASs) from the genome level is the key to understanding the mechanism of translation regulation and …
- 108020004412 RNA 3' Polyadenylation Signals 0 title abstract description 118
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/12—Computer systems based on biological models using genetic models
- G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
-
- 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
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
- G06K9/627—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches based on distances between the pattern to be recognised and training or reference patterns
-
- 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
- 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
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/02—Knowledge representation
- G06N5/022—Knowledge engineering, knowledge acquisition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
- G06N5/04—Inference methods or devices
-
- 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
- G06F17/50—Computer-aided design
-
- 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 |
|---|---|---|
| Guo et al. | Context-aware poly (a) signal prediction model via deep spatial–temporal neural networks | |
| Xie et al. | Self-attention-based BiLSTM model for short text fine-grained sentiment classification | |
| Liu et al. | Human-level control through directly trained deep spiking Q-networks | |
| Huang et al. | Harnessing deep learning for population genetic inference | |
| Xue et al. | A survey on evolutionary computation approaches to feature selection | |
| Li et al. | Expensive optimization via surrogate-assisted and model-free evolutionary optimization | |
| CN112256866B (en) | Text fine-grained emotion analysis algorithm based on deep learning | |
| Li et al. | A bilevel learning model and algorithm for self-organizing feed-forward neural networks for pattern classification | |
| Han et al. | Binary symbiotic organism search algorithm for feature selection and analysis | |
| Tang et al. | From discourse to narrative: Knowledge projection for event relation extraction | |
| CN115472229B (en) | Thermophilic protein prediction method and device | |
| CN117094431A (en) | DWTfar meteorological data time sequence prediction method and equipment for multi-scale entropy gating | |
| Thaher et al. | Teaching learning-based optimization with evolutionary binarization schemes for tackling feature selection problems | |
| Antonelli et al. | Multi-objective evolutionary learning of granularity, membership function parameters and rules of Mamdani fuzzy systems | |
| Cao et al. | Stacked Residual Recurrent Neural Network with Word Weight for Text Classification. | |
| CN117995268A (en) | Interpretable genome selection method and system based on deep learning and heterogeneous network | |
| Guo et al. | Identifying polyadenylation signals with biological embedding via self-attentive gated convolutional highway networks | |
| Elhassani et al. | Deep learning concepts for genomics: an overview | |
| Xue et al. | ASTTN: An Adaptive Spatial–Temporal Transformer Network for traffic flow prediction | |
| CN117033631A (en) | Bidirectional emotion triplet extraction method based on span level and countermeasure training | |
| Cai et al. | Semantic and correlation disentangled graph convolutions for multilabel image recognition | |
| Wang et al. | Ask: Adversarial soft k-nearest neighbor attack and defense | |
| Liu et al. | An efficient differential evolution via both top collective and p-best information | |
| Srivastava et al. | Machine Learning Techniques to Infer Protein Structure and Function from Sequences: A Comprehensive Review | |
| Nethala et al. | GECC-Net: Gene Expression-Based Cancer Classification using Hybrid Fuzzy Ranking Network with Multi-kernel SVM |