Cargando…

Prediction of Cell Penetrating Peptides by Support Vector Machines

Cell penetrating peptides (CPPs) are those peptides that can transverse cell membranes to enter cells. Once inside the cell, different CPPs can localize to different cellular components and perform different roles. Some generate pore-forming complexes resulting in the destruction of cells while othe...

Descripción completa

Detalles Bibliográficos
Autores principales:	Sanders, William S., Johnston, C. Ian, Bridges, Susan M., Burgess, Shane C., Willeford, Kenneth O.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2011
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3136433/ https://www.ncbi.nlm.nih.gov/pubmed/21779156 http://dx.doi.org/10.1371/journal.pcbi.1002101

Ejemplares similares

Prediction of peptides observable by mass spectrometry applied at the experimental set level
por: Sanders, William S, et al.
Publicado: (2007)

A Genetic Algorithm Based Support Vector Machine Model for Blood-Brain Barrier Penetration Prediction
por: Zhang, Daqing, et al.
Publicado: (2015)

Krein support vector machine classification of antimicrobial peptides
por: Redshaw, Joseph, et al.
Publicado: (2023)

Machine Learning To Predict Cell-Penetrating Peptides for Antisense Delivery
por: Wolfe, Justin M., et al.
Publicado: (2018)

Prediction of Functional Class of Proteins and Peptides Irrespective of Sequence Homology by Support Vector Machines
por: Tang, Zhi Qun, et al.
Publicado: (2009)

Disruptin, a cell-penetrating peptide degrader of EGFR: Cell-Penetrating Peptide in Cancer Therapy
por: Mehta, Ranjit K., et al.
Publicado: (2021)

Cell-Penetrating Peptides: Efficient Vectors for Vaccine Delivery
por: Yang, Jieru, et al.
Publicado: (2019)

Cell Penetrating Peptides, Novel Vectors for Gene Therapy
por: Taylor, Rebecca E., et al.
Publicado: (2020)

Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine
por: Xu, Yongtao, et al.
Publicado: (2015)

Support Vector Machines
por: Deng, Naiyang
Publicado: (2012)

Support vector machines
por: Steinwart, Ingo, et al.
Publicado: (2008)

Support Vector Machines for predicting protein structural class
por: Cai, Yu-Dong, et al.
Publicado: (2001)

Applications and Challenges for Use of Cell-Penetrating Peptides as Delivery Vectors for Peptide and Protein Cargos
por: Kristensen, Mie, et al.
Publicado: (2016)

Incorporating support vector machine with sequential minimal optimization to identify anticancer peptides
por: Wan, Yu, et al.
Publicado: (2021)

Predicting cell-penetrating peptides using machine learning algorithms and navigating in their chemical space
por: de Oliveira, Ewerton Cristhian Lima, et al.
Publicado: (2021)

Novel Lung Targeting Cell Penetrating Peptides as Vectors for Delivery of Therapeutics
por: McCandless, Kayla, et al.
Publicado: (2021)

Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs)
por: Rausch, Christian, et al.
Publicado: (2005)

Prediction of Antimicrobial Peptides Based on Sequence Alignment and Support Vector Machine-Pairwise Algorithm Utilizing LZ-Complexity
por: Ng, Xin Yi, et al.
Publicado: (2015)

Understanding support vector machines
por: Géron, Aurélien
Publicado: (2017)

Learning with Support Vector Machines
por: Campbell, Colin, et al.
Publicado: (2010)

Support vector machines applications
por: Ma, Yunqian, et al.
Publicado: (2014)

Accurate splice site prediction using support vector machines
por: Sonnenburg, Sören, et al.
Publicado: (2007)

Profiled support vector machines for antisense oligonucleotide efficacy prediction
por: Camps-Valls, Gustavo, et al.
Publicado: (2004)

Transmembrane protein topology prediction using support vector machines
por: Nugent, Timothy, et al.
Publicado: (2009)

Prediction of Protein Essentiality by the Support Vector Machine with Statistical Tests
por: Hor, Chiou-Yi, et al.
Publicado: (2013)

Support vector machine classifier for prediction of the metastasis of colorectal cancer
por: Zhi, Jiajun, et al.
Publicado: (2018)

Weighted K-means support vector machine for cancer prediction
por: Kim, SungHwan
Publicado: (2016)

Prediction of Transmembrane Proteins from Their Primary Sequence by Support Vector Machine Approach
por: Cai, C. Z., et al.
Publicado: (2006)

Recent Advances of Cell-Penetrating Peptides and Their Application as Vectors for Delivery of Peptide and Protein-Based Cargo Molecules
por: Zhang, Huifeng, et al.
Publicado: (2023)

The Luminescence Hypothesis of Olfaction
por: Willeford, Kenneth
Publicado: (2023)

Glycosylation site prediction using ensembles of Support Vector Machine classifiers
por: Caragea, Cornelia, et al.
Publicado: (2007)

Predicting post-translational lysine acetylation using support vector machines
por: Gnad, Florian, et al.
Publicado: (2010)

Predicting siRNA potency with random forests and support vector machines
por: Wang, Liangjiang, et al.
Publicado: (2010)

Prediction of Drosophila melanogaster gene function using Support Vector Machines
por: Mitsakakis, Nicholas, et al.
Publicado: (2013)

Prediction of Protein–Protein Interaction with Pairwise Kernel Support Vector Machine
por: Zhang, Shao-Wu, et al.
Publicado: (2014)

Scatter-search with support vector machine for prediction of relative solvent accessibility
por: Kashefi, Amir Hosein, et al.
Publicado: (2013)

Application of the Support Vector Machine to Predict Subclinical Mastitis in Dairy Cattle
por: Mammadova, Nazira, et al.
Publicado: (2013)

Applications of Support Vector Machine in Genomic Prediction in Pig and Maize Populations
por: Zhao, Wei, et al.
Publicado: (2020)

Churn prediction in telecommunication industry using kernel Support Vector Machines
por: Y., Nguyen Nhu, et al.
Publicado: (2022)

mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides
por: Boopathi, Vinothini, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_5411d4as991am7e0q9u70os28v