What do you want to do with model?
Choose the purpose of deep learning model you want to design.
Feature extraction
A process of reducing the dimension of dataset by summarizing original features into new informative and non-redundant features.
The extracted features can be used to data clustering.
Data generation
A process of generating the synthetic data that mimics the input dataset.
The generative model conducts the process for learning the patterns in input dataset to generate data.
Classification
The process of organizing data into pre-defined categories based on the features of data.
* It requires the label data (pre-defined categories) *
Regression
The process of investigating the relationship between a dependent (outcomes) and independent variables (features).
* It requires the label data (outcomes) *
Which data do you have?
Choose input data to use training and testing deep learning model.
Matrix data
(Text file)
Sequence data
(FASTA format)
Mapping data
(BAM format)
Annotation data
(GFF format)
Position data
(BED format)
Profile / signal data
(bigWig format)
