fitsvm matlab function Search Results


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MathWorks Inc matlab fitsvm function
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MathWorks Inc fitsvm function
Fitsvm Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc svm matlab 2018b fitsvm function
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MathWorks Inc fitsvm
Fitsvm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc support vector machine classifiers radial basis function kernels
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MathWorks Inc fitrensemble
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MathWorks Inc function fitscvm
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MathWorks Inc svmtrain function
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MathWorks Inc svm
( A ) Maximum likelihood tree obtained with the whole genome <t>nucleotide</t> sequences alignment of alpha-HPV, colored by the different alpha-class categories. ( B ) Maximum likelihood trees obtained with alignments of E6, E7, E1, E2, L1 and L2 amino acid sequences of alpha-HPV, colored by the oncogenic risk groups.
Svm, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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MathWorks Inc functions fitsvm and cvpartition
( A ) Maximum likelihood tree obtained with the whole genome <t>nucleotide</t> sequences alignment of alpha-HPV, colored by the different alpha-class categories. ( B ) Maximum likelihood trees obtained with alignments of E6, E7, E1, E2, L1 and L2 amino acid sequences of alpha-HPV, colored by the oncogenic risk groups.
Functions Fitsvm And Cvpartition, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


( A ) Maximum likelihood tree obtained with the whole genome nucleotide sequences alignment of alpha-HPV, colored by the different alpha-class categories. ( B ) Maximum likelihood trees obtained with alignments of E6, E7, E1, E2, L1 and L2 amino acid sequences of alpha-HPV, colored by the oncogenic risk groups.

Journal: F1000Research

Article Title: A unique insert in the genomes of high-risk human papillomaviruses with a predicted dual role in conferring oncogenic risk

doi: 10.12688/f1000research.19590.2

Figure Lengend Snippet: ( A ) Maximum likelihood tree obtained with the whole genome nucleotide sequences alignment of alpha-HPV, colored by the different alpha-class categories. ( B ) Maximum likelihood trees obtained with alignments of E6, E7, E1, E2, L1 and L2 amino acid sequences of alpha-HPV, colored by the oncogenic risk groups.

Article Snippet: To apply Support Vector Machines (SVM , using Matlab 2018b fitsvm function) to the nucleotide sequences, we first encoded the data with numbers, where each nucleotide is coded as ‘1’ and each gap as ‘0’.

Techniques:

( A ) Nucleotide sequence alignment of alpha-HPVs (blue, LR-HPV; orange, HR-HPV sequences). Arrows: Grey, E7 start codon for most HPV types; Blue and Orange, E6 stop codons that are distinct between LR-HPV and HR-HPV. ( B ) Alignment of the C-terminal amino acid sequences of E6 proteins of alpha-HPVs. ( C ) Schematic representation of the E6/E7 separation caused by the insertion in the 3’-terminal region of E6 and the proximity of E6 stop and E7 starts in HR-HPV.

Journal: F1000Research

Article Title: A unique insert in the genomes of high-risk human papillomaviruses with a predicted dual role in conferring oncogenic risk

doi: 10.12688/f1000research.19590.2

Figure Lengend Snippet: ( A ) Nucleotide sequence alignment of alpha-HPVs (blue, LR-HPV; orange, HR-HPV sequences). Arrows: Grey, E7 start codon for most HPV types; Blue and Orange, E6 stop codons that are distinct between LR-HPV and HR-HPV. ( B ) Alignment of the C-terminal amino acid sequences of E6 proteins of alpha-HPVs. ( C ) Schematic representation of the E6/E7 separation caused by the insertion in the 3’-terminal region of E6 and the proximity of E6 stop and E7 starts in HR-HPV.

Article Snippet: To apply Support Vector Machines (SVM , using Matlab 2018b fitsvm function) to the nucleotide sequences, we first encoded the data with numbers, where each nucleotide is coded as ‘1’ and each gap as ‘0’.

Techniques: Sequencing