4.7 Article

AFP-CMBPred: Computational identification of antifreeze proteins by extending consensus sequences into multi-blocks evolutionary information

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

Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks

Ashfaq Ahmad et al.

Summary: Fungal infections have become a serious global issue, making accurate identification of antifungal peptides challenging for researchers. A high-performance intelligent model, DeepAntiFP, was proposed and demonstrated to outperform existing computational models in antifungal peptide identification.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2021)

Article Biology

iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model

Shahid Akbar et al.

Summary: This study proposes the use of an intelligent and reliable prediction model for identifying antitubercular peptides, using an ensemble learning approach to improve results. The approach aims to compensate for the shortcomings of individual classification algorithms and show promising results in accurately predicting tuberculosis.

COMPUTERS IN BIOLOGY AND MEDICINE (2021)

Article Computer Science, Information Systems

piEnPred: a bi-layered discriminative model for enhancers and their subtypes via novel cascade multi-level subset feature selection algorithm

Zaheer Ullah Khan et al.

Summary: The study focused on the prediction of enhancers by building a more robust computational bi-layered model. The first layer accurately predicts enhancers, while the second layer predicts their subtypes. The proposed method outperformed other state-of-the-art predictors and a user-friendly web server has been developed for accessibility to experimental scientists.

FRONTIERS OF COMPUTER SCIENCE (2021)

Article Biochemical Research Methods

DBP-GAPred: An intelligent method for prediction of DNA-binding proteins types by enhanced evolutionary profile features with ensemble learning

Omar Barukab et al.

Summary: This study extends the feature extraction method for protein sequences and trains a model using SVM to improve the prediction performance of DNA-binding proteins. The new predictor achieved higher accuracies than existing predictors, demonstrating the superiority of the method.

JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY (2021)

Article Computer Science, Information Systems

iRNA-PseTNC: identification of RNA 5-methylcytosine sites using hybrid vector space of pseudo nucleotide composition

Shahid Akbar et al.

FRONTIERS OF COMPUTER SCIENCE (2020)

Article Automation & Control Systems

cACP: Classifying anticancer peptides using discriminative intelligent model via Chou's 5-step rules and general pseudo components

Shahid Akbar et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2020)

Article Biochemistry & Molecular Biology

TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree

Muhammad Arif et al.

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2020)

Article Automation & Control Systems

iHBP-DeepPSSM: Identifying hormone binding proteins using PsePSSM based evolutionary features and deep learning approach

Shahid Akbar et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2020)

Review Chemistry, Organic

A Brief Review of the Computational Identification of Antifreeze Protein

Fang Wang et al.

CURRENT ORGANIC CHEMISTRY (2019)

Article Biochemical Research Methods

Prediction of membrane protein types by exploring local discriminative information from evolutionary profiles

Muhammad Kabir et al.

ANALYTICAL BIOCHEMISTRY (2019)

Article Automation & Control Systems

Improving prediction of extracellular matrix proteins using evolutionary information via a grey system model and asymmetric under-sampling technique

Muhammad Kabir et al.

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2018)

Article Pharmacology & Pharmacy

AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest

Balachandran Manavalan et al.

FRONTIERS IN PHARMACOLOGY (2018)

Article Biochemical Research Methods

An Integrated Feature Selection Algorithm for Cancer Classification using Gene Expression Data

Saeed Ahmed et al.

COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING (2018)

Article Mathematical & Computational Biology

Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine

Saeed Ahmed et al.

INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS (2018)

Article Multidisciplinary Sciences

afpCOOL: A tool for antifreeze protein prediction

Morteza Eslami et al.

HELIYON (2018)

Article Computer Science, Artificial Intelligence

Mining DNA Sequence Patterns with Constraints Using Hybridization of Firefly and Group Search Optimization

Kuruva Lakshmanna et al.

JOURNAL OF INTELLIGENT SYSTEMS (2018)

Article Computer Science, Information Systems

Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information

Leyi Wei et al.

INFORMATION SCIENCES (2017)

Article Biochemistry & Molecular Biology

PSFM-DBT: Identifying DNA-Binding Proteins by Combing Position Specific Frequency Matrix and Distance-Bigram Transformation

Jun Zhang et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2017)

Article Chemistry, Multidisciplinary

CryoProtect: A Web Server for Classifying Antifreeze Proteins from Nonantifreeze Proteins

Reny Pratiwi et al.

JOURNAL OF CHEMISTRY (2017)

Article Computer Science, Artificial Intelligence

iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space

Shahid Akbar et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2017)

Article Biochemistry & Molecular Biology

iAFP-Ense: An Ensemble Classifier for Identifying Antifreeze Protein by Incorporating Grey Model and PSSM into PseAAC

Xuan Xiao et al.

JOURNAL OF MEMBRANE BIOLOGY (2016)

Article Biochemistry & Molecular Biology

An Effective Antifreeze Protein Predictor with Ensemble Classifiers and Comprehensive Sequence Descriptors

Runtao Yang et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2015)

Article Biotechnology & Applied Microbiology

Harnessing Computational Biology for Exact Linear B-Cell Epitope Prediction: A Novel Amino Acid Composition-Based Feature Descriptor

Vijayakumar Saravanan et al.

OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY (2015)

Article Biology

Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction

Sukanta Mondal et al.

JOURNAL OF THEORETICAL BIOLOGY (2014)

Article Biochemistry & Molecular Biology

Using Support Vector Machine and Evolutionary Profiles to Predict Antifreeze Protein Sequences

Xiaowei Zhao et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2012)

Article Biology

AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties

Krishna Kumar Kandaswamy et al.

JOURNAL OF THEORETICAL BIOLOGY (2011)

Article Multidisciplinary Sciences

Lateral Transfer of a Lectin-Like Antifreeze Protein Gene in Fishes

Laurie A. Graham et al.

PLOS ONE (2008)

Article Biochemical Research Methods

Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences

Weizhong Li et al.

BIOINFORMATICS (2006)

Review Biochemistry & Molecular Biology

Antifreeze proteins: an unusual receptor-ligand interaction

ZC Jia et al.

TRENDS IN BIOCHEMICAL SCIENCES (2002)