4.5 Article

iPromoter-ET: Identifying promoters and their strength by extremely randomized trees-based feature selection

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Automation & Control Systems

PA-PseU: An incremental passive-aggressive based method for identifying RNA pseudouridine sites via Chou's 5-steps rule

Jiesheng Wang et al.

Summary: In this article, an incremental identification method called PA-PseU, based on Passive-Aggressive algorithm, is proposed for identifying pseudouridine ('P) sites in RNA. Experimental validation shows that the method outperforms previous approaches in terms of accuracy and efficiency.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2021)

Article Biochemistry & Molecular Biology

PPD: A Manually Curated Database for Experimentally Verified Prokaryotic Promoters

Wei Su et al.

Summary: This study established a Prokaryotic Promoter Database (PPD) which manually extracted 129,148 experimentally validated promoters across 63 prokaryotic species from published papers, providing users with a user-friendly interface for browsing, searching, visualizing, submitting, and downloading data.

JOURNAL OF MOLECULAR BIOLOGY (2021)

Article Chemistry, Multidisciplinary

iORI-ENST: identifying origin of replication sites based on elastic net and stacking learning

Y. Yao et al.

Summary: DNA replication is fundamental in all living organisms and plays a crucial role in cell division and gene expression. Identifying replication origin sites is important for understanding gene regulation mechanisms and treating genetic diseases. A novel iORI-ENST model was developed using feature extraction, selection, and stacking learning to accurately identify ORIs with high accuracy.

SAR AND QSAR IN ENVIRONMENTAL RESEARCH (2021)

Article Biochemistry & Molecular Biology

Use Chou's 5-steps rule to identify DNase I hypersensitive sites via dinucleotide property matrix and extreme gradient boosting

Shengli Zhang et al.

MOLECULAR GENETICS AND GENOMICS (2020)

Article Biochemical Research Methods

Identifying Sigma70 Promoters with Novel Pseudo Nucleotide Composition

Hao Lin et al.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2019)

Article Biochemical Research Methods

StackDPPred: a stacking based prediction of DNA-binding protein from sequence

Avdesh Mishra et al.

BIOINFORMATICS (2019)

Article Biochemical Research Methods

Enhancer-5Step: Identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding

Nguyen Quoc Khanh Le et al.

ANALYTICAL BIOCHEMISTRY (2019)

Article Medicine, Research & Experimental

iProEP: A Computational Predictor for Predicting Promoter

Hong-Yan Lai et al.

MOLECULAR THERAPY-NUCLEIC ACIDS (2019)

Article Genetics & Heredity

iDNA6mA-Rice: A Computational Tool for Detecting N6-Methyladenine Sites in Rice

Hao Lv et al.

FRONTIERS IN GENETICS (2019)

Article Biochemical Research Methods

iEnhancer-EL: identifying enhancers and their strength with ensemble learning approach

Bin Liu et al.

BIOINFORMATICS (2018)

Article Biochemistry & Molecular Biology

iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree

Shaherin Basith et al.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2018)

Article Biochemical Research Methods

iRSpot-EL: identify recombination spots with an ensemble learning approach

Bin Liu et al.

BIOINFORMATICS (2017)

Article Biochemical Research Methods

MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis

Joao F. Matias Rodrigues et al.

BIOINFORMATICS (2017)

Article Biochemistry & Molecular Biology

RegulonDB version 9.0: high-level integration of gene regulation, coexpression, motif clustering and beyond

Socorro Gama-Castro et al.

NUCLEIC ACIDS RESEARCH (2016)

Article Biochemical Research Methods

pRNAm-PC: Predicting N6-methyladenosine sites in RNA sequences via physical-chemical properties

Zi Liu et al.

ANALYTICAL BIOCHEMISTRY (2016)

Review Microbiology

Bacterial Sigma Factors: A Historical, Structural, and Genomic Perspective

Andrey Feklistov et al.

ANNUAL REVIEW OF MICROBIOLOGY, VOL 68 (2014)

Article Biochemical Research Methods

CD-HIT: accelerated for clustering the next-generation sequencing data

Limin Fu et al.

BIOINFORMATICS (2012)

Article Biochemistry & Molecular Biology

Recognition of prokaryotic promoters based on a novel variable-window Z-curve method

Kai Song

NUCLEIC ACIDS RESEARCH (2012)

Article Biochemical Research Methods

TopHat: discovering splice junctions with RNA-Seq

Cole Trapnell et al.

BIOINFORMATICS (2009)

Review Biochemical Research Methods

Recent progress in protein subcellular location prediction

Kuo-Chen Chou et al.

ANALYTICAL BIOCHEMISTRY (2007)

Article Biology

The recognition and prediction of σ70 promoters in Escherichia coli K-12

Qian-Zhong Li et al.

JOURNAL OF THEORETICAL BIOLOGY (2006)

Article Computer Science, Artificial Intelligence

Extremely randomized trees

P Geurts et al.

MACHINE LEARNING (2006)

Article Biochemistry & Molecular Biology

DBTSS: DataBase of human transcriptional start sites and full-length cDNAs

Y Suzuki et al.

NUCLEIC ACIDS RESEARCH (2002)