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MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition

A. Hoglund, P. Donnes, T. Blum, H.-W. Adolph, O. Kohlbacher
2006 Bioinformatics  
Results: Here we present a novel SVM-based approach for predicting subcellular localization, which integrates N-terminal targeting sequences, amino acid composition and protein sequence motifs.  ...  We show how this approach improves the prediction based on N-terminal targeting sequences, by comparing our method TargetLoc against existing methods.  ...  The approach considers N-terminal targeting sequences, amino acid composition and the presence of specific protein sequence motifs obtained from established motif databases.  ... 
doi:10.1093/bioinformatics/btl002 pmid:16428265 fatcat:6f3ef77ci5gbzhlfylzzg5vi7e

EuLoc: a web-server for accurately predict protein subcellular localization in eukaryotes by incorporating various features of sequence segments into the general form of Chou's PseAAC

Tzu-Hao Chang, Li-Ching Wu, Tzong-Yi Lee, Shu-Pin Chen, Hsien-Da Huang, Jorng-Tzong Horng
2013 Journal of Computer-Aided Molecular Design  
The proposed HMM modules overcome the shortcoming of SVM in predicting subcellular localizations using few data on protein sequences.  ...  acid composition.  ...  [12] Two-layer SVM N-terminal targeting peptide, single anchor (SA), amino acid composition, motifs from PROSITE and NLSdb Fungi: 9 Animal: 9 Plant: 10 Hoglund et al. [12] BaCelLo [13]  ... 
doi:10.1007/s10822-012-9628-0 pmid:23283513 fatcat:naws5mt22vh73j46e77sgqqyau

Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences

Kenichiro Imai, Kenta Nakai
2020 Frontiers in Genetics  
Thus, it is interesting to computationally recognize these signals from the amino acid sequences of any given proteins and to predict their final subcellular localization with such information, supplemented  ...  At the time of translation, nascent proteins are thought to be sorted into their final subcellular localization sites, based on the part of their amino acid sequences (i.e., sorting or targeting signals  ...  Such empirical features include the frequency of dipeptides, n-grams, and k-mers as well as the pseudo amino acid composition of the entire amino acid sequence (or that of predicted mature sequence).  ... 
doi:10.3389/fgene.2020.607812 pmid:33324450 pmcid:PMC7723863 fatcat:nfamzbspyvbrpd6bqwt5nryzqm

Predicting Protein Subcellular Localization: Past, Present, and Future

Pierre Dönnes, Annette Höglund
2004 Genomics, Proteomics & Bioinformatics  
Predicting the subcellular localization by computational means has been an area of vivid activity during recent years.  ...  The publicly available prediction methods differ mainly in four aspects: the underlying biological motivation, the computational method used, localization coverage, and reliability, which are of importance  ...  PSORT uses the overall amino acid composition, N-terminal targeting sequence information, and motifs, hence considered a hybrid approach.  ... 
doi:10.1016/s1672-0229(04)02027-3 fatcat:z45jw5iojvga3ikcwlgs77cgpm

PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization

Kenta Nakai, Paul Horton
1999 TIBS -Trends in Biochemical Sciences. Regular ed  
Acknowledgements We thank the Ministry of Education, Science and Culture, Japan, for support.  ...  We also thank Toshiki Ohkawa, Tomoki Miwa and Atsushi Ogiwara for maintaining a Web server at the National Institute for Basic Biology.  ...  signal peptide Modified McGeoch's method and the cleavage-site 10, 11 consensus Mitochondrial-targeting signal Amino acid composition of the N-terminal 20 residues 5, 12 and some weak cleavage-site  ... 
doi:10.1016/s0968-0004(98)01336-x pmid:10087920 fatcat:nxlkgdrzhzakhiwezkg3x7ufmy

Signal peptides and protein localization prediction [chapter]

Henrik Nielsen
2005 Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics  
Acknowledgments I thank Gunnar von Heijne and Jacob Engelbrecht for comments on the manuscript.  ...  ., 2004) uses the amino acid composition of the first and last half of each sequence and distinguishes between eight subcellular locations.  ...  There is a rapidly growing number of subcellular localization prediction methods based on amino acid composition and related features.  ... 
doi:10.1002/047001153x.g403409 fatcat:3gf2h7cdcnhpjaeuy6amqyjude

A novel representation of protein sequences for prediction of subcellular location using support vector machines

Setsuro Matsuda, Jean-Philippe Vert, Hiroto Saigo, Nobuhisa Ueda, Hiroyuki Toh, Tatsuya Akutsu
2005 Protein Science  
This representation involves local compositions of amino acids and twin amino acids, and local frequencies of distance between successive (basic, hydrophobic, and other) amino acids.  ...  For calculating the local features, each sequence is split into three parts: Nterminal, middle, and C-terminal.  ...  Bill Pearson for the help about the usage of the FASTA package and Dr. Morihiro Hayashida of Kyoto University for valuable comments.  ... 
doi:10.1110/ps.051597405 pmid:16251364 pmcid:PMC2253224 fatcat:cwnfr4e6ofa2nezfxry7lxmevq

TESTLoc: protein subcellular localization prediction from EST data

Yao-Qing Shen, Gertraud Burger
2010 BMC Bioinformatics  
Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties.  ...  Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life.  ...  Acknowledgements We would like to thank Geneviève Galarneau for programming parts of TESTLoc and evaluating the accuracy of ORF prediction, and Jean-François Théroux for implementing gapped amino acid  ... 
doi:10.1186/1471-2105-11-563 pmid:21078192 pmcid:PMC3000424 fatcat:xk2ht7hoznabdkdsobwmy55nmi

Implicit motif distribution based hybrid computational kernel for sequence classification

V. Atalay, R. Cetin-Atalay
2004 Bioinformatics  
P2SL hybrid computational system achieved ∼81% of prediction accuracy rate over ER targeted, cytosolic, mitochondrial and nuclear protein localization classes.  ...  Instead of searching for explicit motifs, our approach finds the distribution of implicit motifs and uses as a feature for classification.  ...  Ozturk (Bilkent University, Turkey) for his critical discussions on this paper and M. Ozarar for the initial technical assistance. This work was supported by the Turkish Academy of Sciences to R.C.A.  ... 
doi:10.1093/bioinformatics/bti212 pmid:15598837 fatcat:7khtollt3ndy5ohfpkvcp26rgi

Prediction of organellar targeting signals

Olof Emanuelsson, Gunnar von Heijne
2001 BBA - Molecular Cell Research  
The subcellular location of a protein is an important characteristic with functional implications, and hence the problem of predicting subcellular localization from the amino acid sequence has received  ...  sorting potential of the cell and assign the most likely subcellular localization to a protein based on its amino acid sequence.  ...  Introduction The general problem to predict the subcellular location of a protein from its amino acid sequence has long been a central one in bioinformatics.  ... 
doi:10.1016/s0167-4889(01)00145-8 pmid:11750667 fatcat:ifpuqlk5jnbn5gg6vt3ggqjs4u

RSLpred: an integrative system for predicting subcellular localization of rice proteins combining compositional and evolutionary information

Rakesh Kaundal, Gajendra P. S. Raghava
2009 Proteomics  
In this study, a large number of modules have been developed using various encoding schemes like higher-order dipeptide composition, N-and C-terminal, splitted amino acid composition and the hybrid information  ...  First, the support vector machine (SVM)-based modules have been developed using traditional amino acid-, dipeptide-(i11) and four parts-amino acid composition and achieved an overall accuracy of 81.43,  ...  25 residues used as input; SAAC, whole protein is divided into three parts, N-terminal 25 amino acids, C-terminal 25 amino acids and remaining sequence.  ... 
doi:10.1002/pmic.200700597 pmid:19402042 fatcat:iud64h4fozbjzh32tim3344bqq

Plant-mSubP: a computational framework for the prediction of single- and multi-target protein subcellular localization using integrated machine-learning approaches

2019 AoB Plants  
Using the hybrid feature of the pseudo amino acid composition, N-Center-C terminal amino acid composition and the dipeptide composition (PseAAC-NCC-DIPEP), an overall accuracy of 81.97 %, 84.75 % and 87.88  ...  Several hybrid features based on composition and physicochemical properties of a protein such as amino acid composition, pseudo amino acid composition, auto-correlation descriptors, quasi-sequence-order  ...  Acknowledgements The authors acknowledge the support to this study from faculty start-up funds to R.K. from the Center for Integrated BioSystems/Department of Plants, Soils, and Climate, Utah State University  ... 
doi:10.1093/aobpla/plz068 pmid:32528639 pmcid:PMC7274489 fatcat:pcksqe5un5acpiee7vbf4nst7e

PROlocalizer: integrated web service for protein subcellular localization prediction

Kirsti Laurila, Mauno Vihinen
2010 Amino Acids  
Subcellular localization is an important protein property, which is related to function, interactions and other features.  ...  We developed the PROlocalizer service that integrates 11 individual methods to predict altogether 12 localizations for animal proteins.  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided  ... 
doi:10.1007/s00726-010-0724-y pmid:20811800 pmcid:PMC3040813 fatcat:ishdcrez6vbzbcrcgtcapbl3ci

Identification of Proteins Secreted by Malaria Parasite into Erythrocyte using SVM and PSSM profiles

Ruchi Verma, Ajit Tiwari, Sukhwinder Kaur, Grish C Varshney, Gajendra PS Raghava
2008 BMC Bioinformatics  
We developed SVM models and achieved maximum MCC 0.72 with 85.65% accuracy and MCC 0.74 with 86.45% accuracy using amino acid and dipeptide composition respectively.  ...  SVM models were developed using split-amino acid and split-dipeptide composition and achieved maximum MCC 0.74 with 86.40% accuracy and MCC 0.77 with accuracy 88.22% respectively.  ...  Acknowledgements The authors are thankful to the Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT), Government of India for financial assistance.  ... 
doi:10.1186/1471-2105-9-201 pmid:18416838 pmcid:PMC2358896 fatcat:uflc3jclvnbpri7xuh3y6gppgm

Identification of peptide domains involved in the subcellular localization of the feline coronavirus 3b protein

Delphine D. Acar, Veerle J. E. Stroobants, Herman Favoreel, Xavier Saelens, Hans J. Nauwynck
2019 Journal of General Virology  
FCoV open reading frame 3 (ORF3) encodes accessory proteins 3a, 3b and 3 c. The FCoV 3b accessory protein consists of 72 amino acid residues and localizes to nucleoli and mitochondria.  ...  Mutational analysis also revealed that mitochondrial translocation is mediated by N-terminal residues 10-35, in which a Tom20 recognition motif (residues 13-17) and two other overlapping hexamers (residues  ...  Acknowledgements The authors gratefully acknowledge Ytse Noppe and Marthe Pauwels for their skillful technical assistance.  ... 
doi:10.1099/jgv.0.001321 pmid:31483243 pmcid:PMC7079696 fatcat:tfymo2xm4ndzleqsvwzbpot62m
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