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Prediction of Protein Subcellular Localization Based on Primary Sequence Data [chapter]

Mert Özarar, Volkan Atalay, Rengül Çetin Atalay
2003 Lecture Notes in Computer Science  
A system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based on the amino acid content of primary sequences  ...  pages Subcellular localization is crucial for determining the functions of proteins.  ...  The aim of this work is to design and develop a system called prediction of protein subcellular localization (P2SL) that predicts the subcellular localization of proteins in eukaryotic organisms based  ... 
doi:10.1007/978-3-540-39737-3_76 fatcat:2b2jcni5tjemralp2sdfhqyrcu

LOCATE: a mammalian protein subcellular localization database

J. Sprenger, J. Lynn Fink, S. Karunaratne, K. Hanson, N. A. Hamilton, R. D. Teasdale
2007 Nucleic Acids Research  
Other additions include computational subcellular localization predictions, automated computational classification of experimental localization image data, prediction of protein sorting signals and third  ...  LOCATE is a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of mouse and human proteins.  ...  Funding to pay the Open Access publication charges for this article was provided by The University of Queensland.  ... 
doi:10.1093/nar/gkm950 pmid:17986452 pmcid:PMC2238969 fatcat:rh5sf5cp35aclbdt7fmdwkoohe

FGsub: Fusarium graminearum protein subcellular localizations predicted from primary structures

Chenglei Sun, Xing-Ming Zhao, Weihua Tang, Luonan Chen
2010 BMC Systems Biology  
Subsequently, Support Vector Machine (SVM) is trained on the training set and used to predict F. graminearum protein subcellular localizations for those proteins that do not have significant sequence similarity  ...  Results: In this paper, we developed a novel predictor, namely FGsub, to predict F. graminearum protein subcellular localizations from the primary structures.  ...  Based on the methods described above, we developed a novel predictor, namely FGsub, to predict F. graminearum protein subcellular localizations from the primary structures, i.e. protein sequences.  ... 
doi:10.1186/1752-0509-4-s2-s12 pmid:20840726 pmcid:PMC2982686 fatcat:fx5ytlffcfennebprnuihnoscy

Predicting Protein Subcellular Localization: Past, Present, and Future

Pierre Dönnes, Annette Höglund
2004 Genomics, Proteomics & Bioinformatics  
An important step on this way is to determine the subcellular localization of each protein. Eukaryotic cells are divided into subcellular compartments, or organelles.  ...  Predicting the subcellular localization by computational means has been an area of vivid activity during recent years.  ...  The method Pre-dictNLS is a method specialized on recognizing nuclear proteins, based on a collection of nuclear localization sequences (NLSs; ref. 50 ).  ... 
doi:10.1016/s1672-0229(04)02027-3 fatcat:z45jw5iojvga3ikcwlgs77cgpm

DBMLoc: a Database of proteins with multiple subcellular localizations

Song Zhang, Xuefeng Xia, Jincheng Shen, Yun Zhou, Zhirong Sun
2008 BMC Bioinformatics  
Download, search and sequence BLAST tools are also available on the website. Conclusion: DBMLoc is a protein database which collects proteins with more than one subcellular localization annotation.  ...  Subcellular localization information is one of the key features to protein function research. Locating to a specific subcellular compartment is essential for a protein to function efficiently.  ...  In the recent years, some specific subcellular localization databases are constructed based on experimentation, computational prediction or both.  ... 
doi:10.1186/1471-2105-9-127 pmid:18304364 pmcid:PMC2292141 fatcat:wdqrinikava77dyzvza6ulq3sm

Human Protein Subcellular Localization with Integrated Source and Multi-label Ensemble Classifier

Xiaotong Guo, Fulin Liu, Ying Ju, Zhen Wang, Chunyu Wang
2016 Scientific Reports  
The typical protein subcellular location system based on machine learning methods includes the following four basic steps: (1) establishment of protein data set, (2) protein sequence feature extraction  ...  First, several proteins appear in different subcellular structures simultaneously, whereas current methods only predict one protein sequence in one subcellular structure.  ...  F.L.L. helped to collect the protein localization data. Y.J. helped to revise the English. Z.W. participated in the design of the experiments.  ... 
doi:10.1038/srep28087 pmid:27323846 pmcid:PMC4914962 fatcat:6whwbxlrmnd53npijlaft7zohy

DBSubLoc: database of protein subcellular localization

T. Guo
2004 Nucleic Acids Research  
Based on sequence alignment, non-redundant subsets of the database have been built, which may provide useful information for subcellular localization prediction.  ...  Annotations were taken from primary protein databases, model organism genome projects and literature texts, and then were analyzed to dig out the subcellular localization features of the proteins.  ...  Most known protein subcellular localizations are determined by experimental methods and some others can be obtained based on very high sequence similarities.  ... 
doi:10.1093/nar/gkh109 pmid:14681374 pmcid:PMC308843 fatcat:yw4kqhmjpjhk3aotmlzlmvokli

Prediction of Protein Subcellular Localization Based on Fusion of Multi-view Features

Bo Li, Lijun Cai, Bo Liao, Xiangzheng Fu, Pingping Bing, Jialiang Yang
2019 Molecules  
the protein primary sequence, and novel statistics and information theory (NSI) reflecting local position information of the sequence.  ...  The prediction of protein subcellular localization is critical for inferring protein functions, gene regulations and protein-protein interactions.  ...  Conflicts of Interest: The authors confirm that this article content has no conflict of interest.  ... 
doi:10.3390/molecules24050919 fatcat:3wt3wuudbbbwvcedrhwn3ayqte

Prediction of protein subcellular location using a combined feature of sequence

Qing-Bin Gao, Zheng-Zhi Wang, Chun Yan, Yao-Hua Du
2005 FEBS Letters  
Thus, a computational method for properly predicting the subcellular location of proteins would be significant in interpreting the original data produced by the large-scale genome sequencing projects.  ...  To evaluate the prediction performance of this encoding scheme, a jackknife test based on nearest neighbor algorithm was employed.  ...  This work was supported in part by the National Natural Science Foundation of China (No. 60471003).  ... 
doi:10.1016/j.febslet.2005.05.021 pmid:15949806 fatcat:on6p7ynur5ckxdv6akqtw2nxaa

LOCATE: a mouse protein subcellular localization database

J. L. Fink
2006 Nucleic Acids Research  
We present here LOCATE, a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set.  ...  The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing .1700 peer-reviewed publications.  ...  To date, experimental subcellular localization data have been generated for 417 of these selected proteins and localization data based on primary literature review have been gathered for 1752 TUs.  ... 
doi:10.1093/nar/gkj069 pmid:16381849 pmcid:PMC1347432 fatcat:q6iwxmmuhbdldfiq7mmwudpimi

Protein Interactome and Its Application to Protein Function Prediction [chapter]

Woojin Jung, Hyun-Hwan Jeong, KiYoung Lee
2012 Protein-Protein Interactions - Computational and Experimental Tools  
Total measurement counts all the correctly predicted localizations based on the number of real localizations of test data.  ...  Finally, computational prediction methods of protein subcellular localization, especially by exploiting PPI data, are shown. PPI data PPI can be considered as one kind of protein interactome.  ... 
doi:10.5772/38413 fatcat:c5xkgqo7jbfwjbfglwziauhs2i

Combining Experimental and Predicted Datasets for Determination of the Subcellular Location of Proteins in Arabidopsis

J. L. Heazlewood
2005 Plant Physiology  
Using a variety of these programs, based on primary sequence, proteins can be predicted to be localized to the nucleus, mitochondrion, plastid, peroxisome, and endoplasmic reticulum (ER).  ...  This is a database containing more than 60,000 proteins from a range of organisms that are allocated to subcellular locations based on annotation in primary sequence databases, model organism genome projects  ... 
doi:10.1104/pp.105.065532 pmid:16219920 pmcid:PMC1255979 fatcat:cs3pl4y47nfkvjabulcoaqk4ny

mRNALoc: a novel machine-learning based in-silico tool to predict mRNA subcellular localization

Anjali Garg, Neelja Singhal, Ravindra Kumar, Manish Kumar
2020 Nucleic Acids Research  
Here, we describe a novel machine-learning based tool, mRNALoc, to predict five sub-cellular locations of eukaryotic mRNAs using cDNA/mRNA sequences.  ...  Recent evidences suggest that the localization of mRNAs near the subcellular compartment of the translated proteins is a more robust cellular tool, which optimizes protein expression, post-transcriptionally  ...  Named as mRNALoc (acronym for 'mRNA Localization), this tool is based on the experimentally validated localization data of mRNA retrieved from 'RNALocate' (12) .  ... 
doi:10.1093/nar/gkaa385 pmid:32421834 fatcat:5bbmyrxwvvc3zpustrs5caxe4u

TargetDB: a database of peptides targeting proteins to subcellular locations

T. Wei, M. O'Connell
1999 Bioinformatics  
TargetDB is a relational database designed to represent data on protein targeting sequences, mutant signals, subcellular targets and source organisms.  ...  The web interface supports both direct data authoring and database query functions.  ...  The majority of these sequences are predicted; only 103 sequences in the database are based on biochemical experimental data.  ... 
doi:10.1093/bioinformatics/15.9.765 pmid:10498778 fatcat:k2umsqiylfb5lix4wbyo4uyddy

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.  ...  P2SL additionally offers the distribution potential of proteins among localization classes, which is particularly important for proteins, shuttle between nucleus and cytosol.  ...  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
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