4.7 Article

Integrating reduced amino acid composition into PSSM for improving copper ion-binding protein prediction

Related references

Note: Only part of the references are listed.
Article Genetics & Heredity

CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networks

Farnoush Manavi et al.

Summary: DNA-binding proteins play a vital role in biological activity including replication, packing, and reparation of DNA. They can be classified into single-stranded DNA-binding proteins (SSBs) or double-stranded DNA-binding proteins (DSBs) which help determine their function. Despite previous efforts, the prediction accuracy of DSB and SSB remains limited. In this study, a new method called CNN-Pred is proposed, which accurately predicts DSB and SSB using evolutionary-based features extracted from position specific scoring matrix (PSSM) with a 1D-convolutional neural network (CNN) as the classifier. The results show that CNN-Pred improves DSB and SSB prediction accuracies by more than 4% compared to previous studies. CNN-Pred is available as a standalone tool with its source codes on GitHub: https://github.com/MLBC-lab/CNN-Pred.
Article Biochemical Research Methods

A computational framework of routine test data for the cost-effective chronic disease prediction

Mingzhu Liu et al.

Summary: This study developed a cost-effective framework for predicting chronic diseases using routine blood and biochemical test data. The framework achieved high accuracy and identified important markers for different types of chronic diseases.

BRIEFINGS IN BIOINFORMATICS (2023)

Article Biochemistry & Molecular Biology

A cost-effective machine learning-based method for preeclampsia risk assessment and driver genes discovery

Hao Wang et al.

Summary: This study developed a computational biology method using single-cell transcriptome to identify and predict pathological cell subpopulations of early-onset preeclampsia (PE). The TURF_XGB method achieved high accuracy and recall rates in classifying healthy placenta subpopulations, revealing the heterogeneity of placental biology. Additionally, the analysis revealed the involvement of dendritic cells and the role of C1QB and C1QC in mediating inflammation and driving the development of PE. The study also developed a risk stratification card for preeclampsia classification.

CELL AND BIOSCIENCE (2023)

Article Biochemistry & Molecular Biology

The Metal-binding Protein Atlas (MbPA): An Integrated Database for Curating Metalloproteins in All Aspects

Jinzhao Li et al.

Summary: MbPA is the most comprehensive resource for curating metal-binding proteins, containing a large amount of information on metal-binding proteins and species-specific proteins. Analysis of amino acid residue data at metal-binding sites shows that about 80% of metal ions tend to bind to cysteine, aspartic acid, glutamic acid, and histidine. In addition, MbPA includes 6855 potential pathogenic mutations related to metalloprotein. The resource is freely available.

JOURNAL OF MOLECULAR BIOLOGY (2023)

Article Biochemical Research Methods

iProbiotics: a machine learning platform for rapid identification of probiotic properties from whole-genome primary sequences

Yu Sun et al.

Summary: Lactic acid bacteria consortia are commonly found in food and some possess probiotic properties. This study developed a machine learning-based platform using genomic data to identify probiotics. Results showed diverse oligonucleotide composition in probiotic genomes and a bias towards genes/pathways related to probiotic function. The study also created an online bioinformatic tool, iProbiotics, for rapid probiotic screening.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biology

Recognizing protein-metal ion ligands binding residues by random forest algorithm with adding orthogonal properties

Xiaoxiao You et al.

Summary: Accurately identifying protein-metal ion ligand binding residues is crucial for studying protein functions. However, the imbalance between binding and non-binding residues makes it challenging to eliminate false positives in binding residue prediction. In this paper, we studied the binding sites of seven metal ions and introduced ten orthogonal properties to describe the three-dimensional structure information. By optimizing the parameters, we used the Random Forest algorithm to predict ion ligand binding residues. The proposed method showed good prediction results for certain ions, outperforming the IonSeq method.

COMPUTATIONAL BIOLOGY AND CHEMISTRY (2022)

Article Biochemistry & Molecular Biology

THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methyl-guanosine Sites

Watshara Shoombuatong et al.

Summary: In this study, a novel predictor called THRONE was developed to accurately identify m7G sites in the human genome. THRONE utilizes multiple sequence-based features and machine learning classifiers, and combines multiple models through ensemble learning. The proposed method outperformed existing methods in predicting m7G sites.

JOURNAL OF MOLECULAR BIOLOGY (2022)

Article Biochemical Research Methods

TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization

Young-Jun Jeon et al.

Summary: This study presents the first application of the TACOS method to identify the subcellular localization of human lncRNA in 10 different cell types, with comprehensive evaluations and consistent performance compared to other methods.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biochemical Research Methods

Feature-scML: An Open-source Python Package for the Feature Importance Visualization of Single-Cell Omics with Machine Learning

Pengfei Liang et al.

Summary: Feature-scML is an effective toolkit for analyzing single-cell RNA omics datasets, automating the machine learning process, and customizing visual analysis of the results.

CURRENT BIOINFORMATICS (2022)

Article Biochemical Research Methods

Alignment-free metal ion-binding site prediction from protein sequence through pretrained language model and multi-task learning

Qianmu Yuan et al.

Summary: LMetalSite is an alignment-free sequence-based predictor for metal ion-binding sites. It leverages pretrained language models and transformers to improve prediction accuracy, and adopts multi-task learning to compensate for the scarcity of training data and capture the intrinsic similarities between different metal ions.

BRIEFINGS IN BIOINFORMATICS (2022)

Review Biochemistry & Molecular Biology

Research progress of reduced amino acid alphabets in protein analysis and prediction

Yuchao Liang et al.

Summary: This article systematically reviews and summarizes the strategies and methods used in reducing amino acid alphabets and their applications in protein sequence alignment, functional classification, and prediction of structural properties.

COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL (2022)

Article Biochemistry & Molecular Biology

IHEC_RAAC: a online platform for identifying human enzyme classes via reduced amino acid cluster strategy

Hao Wang et al.

Summary: The study developed a new predictor called IHEC_RAAC, which can accurately identify human enzymes and distinguish their functions, with higher accuracy than previous predictors. By using a new feature extraction method and reduced amino acid cluster scheme, the study improved the feature representation ability for protein sequences.

AMINO ACIDS (2021)

Article Biochemical Research Methods

Single-stranded and double-stranded DNA-binding protein prediction using HMM profiles

Ronesh Sharma et al.

Summary: DNA-binding proteins play essential roles in cellular processes, with single-stranded and double-stranded proteins classified based on their interactions with DNA. Computational prediction of these proteins aids in understanding their functions and binding domains. A proposed method using hidden Markov model profiles achieved improved performance compared to benchmark methods, with approximately 3% overall improvement.

ANALYTICAL BIOCHEMISTRY (2021)

Article Biochemical Research Methods

eHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition

Hao Wang et al.

Summary: The study introduced a predictor named eHSCPr for predicting the early stages of HSCs development. By comparing different gene selection methods, F-score captured critical surface markers and SVM analysis achieved an accuracy of over 94%, confirming important markers for HSCs development stages.

BIOINFORMATICS (2021)

Article Biochemistry & Molecular Biology

BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models

Hong-Liang Li et al.

Summary: This study discusses 155 different biological language models for DNA, RNA, and protein sequence analysis, extending them into the BioSeq-BLM system with superior performance in biological sequence analysis. The establishment of a corresponding web server and standalone package aims to assist readers in conducting their own experiments.

NUCLEIC ACIDS RESEARCH (2021)

Article Mathematical & Computational Biology

ANPrAod: Identify Antioxidant Proteins by Fusing Amino Acid Clustering Strategy and N-Peptide Combination

Qilemuge Xi et al.

Summary: Antioxidant proteins play crucial roles in disease control and aging delay, and accurate identification of these proteins is important for drug development. A computational model called ANPrAod was developed in this study, which outperformed existing methods with high accuracy and reliability.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2021)

Article Genetics & Heredity

Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities

Gai-Fang Dong et al.

Summary: Antimicrobial peptides (AMPs) are potential substitutes for antibiotics in new anti-infective drug design. Machine learning algorithms and web servers have been developed to identify AMPs and their functional activities, but there is room for improvement in prediction algorithms. The Reduced Amino Acid Cluster classifier (iAMP-RAAC) effectively evaluates and identifies AMPs with high accuracy, showing promising performance in both training and test datasets. Further feature selection using ANOVA with incremental feature selection improves prediction performance.

FRONTIERS IN GENETICS (2021)

Article Biology

CWLy-SVM: A support vector machine-based tool for identifying cell wall lytic enzymes

Chaolu Meng et al.

COMPUTATIONAL BIOLOGY AND CHEMISTRY (2020)

Article Biology

Predicting protein-peptide binding sites with a deep convolutional neural network

Wafaa Wardah et al.

JOURNAL OF THEORETICAL BIOLOGY (2020)

Article Biotechnology & Applied Microbiology

Prediction of N7-methylguanosine sites in human RNA based on optimal sequence features

Yu-He Yang et al.

GENOMICS (2020)

Article Biochemical Research Methods

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

Avdesh Mishra et al.

BIOINFORMATICS (2019)

Review Biochemical Research Methods

Function determinants of TET proteins: the arrangements of sequence motifs with specific codes

Dongyang Liu et al.

BRIEFINGS IN BIOINFORMATICS (2019)

Article Biochemical Research Methods

iTerm-PseKNC: a sequence-based tool for predicting bacterial transcriptional terminators

Chao-Qin Feng et al.

BIOINFORMATICS (2019)

Article Biochemical Research Methods

MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters

Meng Zhang et al.

BIOINFORMATICS (2019)

Review Pharmacology & Pharmacy

A Survey for Predicting Enzyme Family Classes Using Machine Learning Methods

Jiu-Xin Tan et al.

CURRENT DRUG TARGETS (2019)

Article Biochemical Research Methods

Protein sequence information extraction and subcellular localization prediction with gapped k-Mer method

Yu-hua Yao et al.

BMC BIOINFORMATICS (2019)

Article Mathematical & Computational Biology

RAACBook: a web server of reduced amino acid alphabet for sequence-dependent inference by using Chou's five-step rule

Lei Zheng et al.

DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION (2019)

Review Computer Science, Interdisciplinary Applications

Relief-based feature selection: Introduction and review

Ryan J. Urbanowicz et al.

JOURNAL OF BIOMEDICAL INFORMATICS (2018)

Review Biophysics

Folding of copper proteins: role of the metal?

Candan Arioz et al.

QUARTERLY REVIEWS OF BIOPHYSICS (2018)

Article Physiology

Intersection of Iron and Copper Metabolism in the Mammalian Intestine and Liver

Caglar Doguer et al.

COMPREHENSIVE PHYSIOLOGY (2018)

Article Biochemical Research Methods

PseKRAAC: a flexible web server for generating pseudo K-tuple reduced amino acids composition

Yongchun Zuo et al.

BIOINFORMATICS (2017)

Article Genetics & Heredity

Predicting enhancer activity and variant impact using gkm-SVM

Michael A. Beer

HUMAN MUTATION (2017)

Review Biochemistry & Molecular Biology

Roles of Copper-Binding Proteins in Breast Cancer

Stephanie Blockhuys et al.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2017)

Article Biochemical Research Methods

MetalPredator: a web server to predict iron-sulfur cluster binding proteomes

Yana Valasatava et al.

BIOINFORMATICS (2016)

Article Biochemistry & Molecular Biology

Structure and Function of Cu(I)- and Zn(II)-ATPases

Oleg Sitsel et al.

BIOCHEMISTRY (2015)

Article Mathematical & Computational Biology

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

Ruifeng Xu et al.

BMC SYSTEMS BIOLOGY (2015)

Article Biochemical Research Methods

Feature weight estimation for gene selection: a local hyperlinear learning approach

Hongmin Cai et al.

BMC BIOINFORMATICS (2014)

Article Biochemistry & Molecular Biology

ZincExplorer: an accurate hybrid method to improve the prediction of zinc-binding sites from protein sequences

Zhen Chen et al.

MOLECULAR BIOSYSTEMS (2013)

Article Biochemistry & Molecular Biology

kmer-SVM: a web server for identifying predictive regulatory sequence features in genomic data sets

Christopher Fletez-Brant et al.

NUCLEIC ACIDS RESEARCH (2013)

Article Biochemistry & Molecular Biology

Swfoldrate: Predicting protein folding rates from amino acid sequence with sliding window method

Xiang Cheng et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2013)

Article Biochemical Research Methods

CD-HIT Suite: a web server for clustering and comparing biological sequences

Ying Huang et al.

BIOINFORMATICS (2010)

Article Biochemistry & Molecular Biology

Prediction of 3D metal binding sites from translated gene sequences based on remote-homology templates

Ronen Levy et al.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS (2009)

Article Biochemistry & Molecular Biology

A structural-dynamical characterization of human Cox17

Lucia Banci et al.

JOURNAL OF BIOLOGICAL CHEMISTRY (2008)

Article Biochemistry & Molecular Biology

Metal binding sites in proteins: Identification and characterization by paramagnetic NMR relaxation

MR Jensen et al.

BIOCHEMISTRY (2005)

Article Biochemical Research Methods

PSSM-based prediction of DNA binding sites in proteins

S Ahmad et al.

BMC BIOINFORMATICS (2005)

Article Biochemistry & Molecular Biology

Ctr1 and its role in body copper homeostasis

PA Sharp

INTERNATIONAL JOURNAL OF BIOCHEMISTRY & CELL BIOLOGY (2003)