iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization
Authors
Keywords
-
Journal
NUCLEIC ACIDS RESEARCH
Volume -, Issue -, Pages -
Publisher
Oxford University Press (OUP)
Online
2021-02-26
DOI
10.1093/nar/gkab122
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Sequence‐based Detection of DNA‐binding Proteins using Multiple‐View Features Allied with Feature Selection
- (2020) Liling Zhou et al. Molecular Informatics
- PASSION: an ensemble neural network approach for identifying the binding sites of RBPs on circRNAs
- (2020) Cangzhi Jia et al. BIOINFORMATICS
- Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning
- (2020) Haodong Xu et al. BRIEFINGS IN BIOINFORMATICS
- Prediction of the sequence-specific cleavage activity of Cas9 variants
- (2020) Nahye Kim et al. NATURE BIOTECHNOLOGY
- Deep learning for genomics using Janggu
- (2020) Wolfgang Kopp et al. Nature Communications
- Integration of A Deep Learning Classifier with A Random Forest Approach for Predicting Malonylation Sites
- (2019) Zhen Chen et al. GENOMICS PROTEOMICS & BIOINFORMATICS
- Selene: a PyTorch-based deep learning library for sequence data
- (2019) Kathleen M. Chen et al. NATURE METHODS
- DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks
- (2019) Mostafa Karimi et al. BIOINFORMATICS
- ResPRE: high-accuracy protein contact prediction by coupling precision matrix with deep residual neural networks
- (2019) Yang Li et al. BIOINFORMATICS
- Iterative feature representations improve N4-methylcytosine site prediction
- (2019) Leyi Wei et al. BIOINFORMATICS
- DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines
- (2019) Yi-Heng Zhu et al. Journal of Chemical Information and Modeling
- The Kipoi repository accelerates community exchange and reuse of predictive models for genomics
- (2019) Žiga Avsec et al. NATURE BIOTECHNOLOGY
- Cellular functions of long noncoding RNAs
- (2019) Run-Wen Yao et al. NATURE CELL BIOLOGY
- Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk
- (2019) Jian Zhou et al. NATURE GENETICS
- mCSM-PPI2: predicting the effects of mutations on protein–protein interactions
- (2019) Carlos H M Rodrigues et al. NUCLEIC ACIDS RESEARCH
- DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions
- (2019) Fuhao Zhang et al. PROTEOMICS
- BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches
- (2019) Bin Liu et al. NUCLEIC ACIDS RESEARCH
- Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences
- (2019) Zhen Chen et al. BRIEFINGS IN BIOINFORMATICS
- Machine learning techniques for protein function prediction
- (2019) Rosalin Bonetta et al. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
- 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-methylcytosine Sites in the Mouse Genome
- (2019) Manavalan et al. Cells
- Prediction of drug-target interaction based on protein features using undersampling and feature selection techniques with boosting
- (2019) S.M. Hasan Mahmud et al. ANALYTICAL BIOCHEMISTRY
- Multimodal deep representation learning for protein interaction identification and protein family classification
- (2019) Da Zhang et al. BMC BIOINFORMATICS
- High precision in protein contact prediction using fully convolutional neural networks and minimal sequence features
- (2018) David T Jones et al. BIOINFORMATICS
- OUP accepted manuscript
- (2018) BRIEFINGS IN BIOINFORMATICS
- Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk
- (2018) Jian Zhou et al. NATURE GENETICS
- PANNZER2: a rapid functional annotation web server
- (2018) Petri Törönen et al. NUCLEIC ACIDS RESEARCH
- Quantitative Crotonylome Analysis Expands the Roles of p300 in the Regulation of Lysine Crotonylation Pathway
- (2018) He Huang et al. PROTEOMICS
- Combinatorial Targeting by MicroRNAs Co-ordinates Post-transcriptional Control of EMT
- (2018) Joseph Cursons et al. Cell Systems
- 4mCPred: Machine Learning Methods for DNA N4-methylcytosine sites Prediction
- (2018) Wenying He et al. BIOINFORMATICS
- OUP accepted manuscript
- (2018) BRIEFINGS IN BIOINFORMATICS
- Hot spot prediction in protein-protein interactions by an ensemble system
- (2018) Quanya Liu et al. BMC Systems Biology
- M6AMRFS: Robust Prediction of N6-Methyladenosine Sites With Sequence-Based Features in Multiple Species
- (2018) Xiaoli Qiang et al. Frontiers in Genetics
- Ultradeep Lysine Crotonylome Reveals the Crotonylation Enhancement on Both Histones and Nonhistone Proteins by SAHA Treatment
- (2017) Quan Wu et al. JOURNAL OF PROTEOME RESEARCH
- Large-Scale Identification of Protein Crotonylation Reveals Its Role in Multiple Cellular Functions
- (2017) Wei Wei et al. JOURNAL OF PROTEOME RESEARCH
- PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition
- (2016) Yongchun Zuo et al. BIOINFORMATICS
- Convolutional neural network architectures for predicting DNA–protein binding
- (2016) Haoyang Zeng et al. BIOINFORMATICS
- A comprehensive review and comparison of different computational methods for protein remote homology detection
- (2016) Junjie Chen et al. BRIEFINGS IN BIOINFORMATICS
- Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
- (2016) John G Doench et al. NATURE BIOTECHNOLOGY
- SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features
- (2016) Yuan Zhou et al. NUCLEIC ACIDS RESEARCH
- iEnhancer-2L: a two-layer predictor for identifying enhancers and their strength by pseudok-tuple nucleotide composition
- (2015) Bin Liu et al. BIOINFORMATICS
- Advances in Protein Contact Map Prediction Based on Machine Learning
- (2015) Jiang Xie et al. Medicinal Chemistry
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Predicting effects of noncoding variants with deep learning–based sequence model
- (2015) Jian Zhou et al. NATURE METHODS
- Machine learning applications in genetics and genomics
- (2015) Maxwell W. Libbrecht et al. NATURE REVIEWS GENETICS
- Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences
- (2015) Bin Liu et al. NUCLEIC ACIDS RESEARCH
- Harnessing Computational Biology for Exact Linear B-Cell Epitope Prediction: A Novel Amino Acid Composition-Based Feature Descriptor
- (2015) Vijayakumar Saravanan et al. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY
- Identification and analysis of the N6-methyladenosine in the Saccharomyces cerevisiae transcriptome
- (2015) Wei Chen et al. Scientific Reports
- repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects
- (2014) Bin Liu et al. BIOINFORMATICS
- iDNA-Prot|dis: Identifying DNA-Binding Proteins by Incorporating Amino Acid Distance-Pairs and Reduced Alphabet Profile into the General Pseudo Amino Acid Composition
- (2014) Bin Liu et al. PLoS One
- Oncogenic role of long noncoding RNA AF118081 in anti-benzo[a]pyrene-trans-7,8-dihydrodiol-9,10-epoxide-transformed 16HBE cells
- (2014) Qiaoyuan Yang et al. TOXICOLOGY LETTERS
- iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition
- (2013) Peng-Mian Feng et al. ANALYTICAL BIOCHEMISTRY
- Metalearning: a survey of trends and technologies
- (2013) Christiane Lemke et al. ARTIFICIAL INTELLIGENCE REVIEW
- hCKSAAP_UbSite: Improved prediction of human ubiquitination sites by exploiting amino acid pattern and properties
- (2013) Zhen Chen et al. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS
- Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites
- (2013) Xiang Chen et al. BIOINFORMATICS
- CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model
- (2013) Liguo Wang et al. NUCLEIC ACIDS RESEARCH
- Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts
- (2013) Liang Sun et al. NUCLEIC ACIDS RESEARCH
- Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art
- (2012) Rasna R Walia et al. BMC BIOINFORMATICS
- SUMOhydro: A Novel Method for the Prediction of Sumoylation Sites Based on Hydrophobic Properties
- (2012) Yong-Zi Chen et al. PLoS One
- Identification of 67 Histone Marks and Histone Lysine Crotonylation as a New Type of Histone Modification
- (2011) Minjia Tan et al. CELL
- Discriminative prediction of mammalian enhancers from DNA sequence
- (2011) D. Lee et al. GENOME RESEARCH
- Incorporating Distant Sequence Features and Radial Basis Function Networks to Identify Ubiquitin Conjugation Sites
- (2011) Tzong-Yi Lee et al. PLoS One
- Prediction of Ubiquitination Sites by Using the Composition of k-Spaced Amino Acid Pairs
- (2011) Zhen Chen et al. PLoS One
- A new taxonomy-based protein fold recognition approach based on autocross-covariance transformation
- (2009) Qiwen Dong et al. BIOINFORMATICS
- Data clustering: 50 years beyond K-means
- (2009) Anil K. Jain PATTERN RECOGNITION LETTERS
- Computational identification of ubiquitylation sites from protein sequences
- (2008) Chun-Wei Tung et al. BMC BIOINFORMATICS
- Prediction of integral membrane protein type by collocated hydrophobic amino acid pairs
- (2008) Ke Chen et al. JOURNAL OF COMPUTATIONAL CHEMISTRY
- Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences
- (2008) Yanzhi Guo et al. NUCLEIC ACIDS RESEARCH
- Predicting Human Nucleosome Occupancy from Primary Sequence
- (2008) Shobhit Gupta et al. PLoS Computational Biology
- A survey of kernel and spectral methods for clustering
- (2007) Maurizio Filippone et al. PATTERN RECOGNITION
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search