Twinscan-mars

Август 23, 2022

Содержание

2. Twinscan Twinscan incorporates a pair wise alignment net (with an informant sequence) into its algorithm Twinscan
3. Goals & Methods Exploit the differences in gene characteristics resulting from each individual informant genome Create
4. Mm Gg Xt Rn Cf Pair-wise Informant Set Mouse Informant Set Human Target Sequence
5. Results Successes Successfully predicts alternatively spliced transcripts de novo Scales well Approximately 1.67 transcripts per gene
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Twinscan
Twinscan incorporates a pair wise alignment net (with an informant sequence)

into its algorithm
Twinscan “works” for human gene prediction with almost any mammalian informant (but mice and rats are the most useful)
Prediction characteristics are dependent on the informant

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Goals & Methods
Exploit the differences in gene characteristics resulting from each

individual informant genome
Create closely-related prediction by incorporating mixtures of pair-wise alignment nets into Twinscan
Cluster these predictions as a way to find multiple transcripts from a single gene

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Mm
Gg
Xt
Rn
Cf
Pair-wise Informant Set
Mouse Informant Set
Human Target Sequence

Слайд 5

Results
Successes
Successfully predicts alternatively spliced transcripts de novo
Scales well
Approximately 1.67 transcripts per

gene with the mouse informant set
Sensitive…