I tried to classify protein using its sequences into their families. Can I use deep convolutional models on this purpose even though they use RGB 3 input metrics of an image? Is there any specific way to convert dataset other than the image in order to classify using these models. I'm new to Artificial neural networks, your suggestions are highly appreciated.
1 Answers
First you need to understand that the models you have in mind are tasked with a very difficult problem: Object Recognition in colored images therefore the models used are very big.
Then you need to know the purpose of using CNNs, is to extract as many features as we can from colored images in order to perform detection.
With the knowledge above considered I think classifying protein using its sequences seems achievable with a much more smaller convolutional model. You may need at max 10 layers of convolution. To conclude you should not need a CNN as complex as google inception model.
About your data: There is no rule about CNNs which say you can only use RGB pictures. These pictures are only arrays. If you have any kind of numeric data which can be used in algorithmic operations ofcourse, you can definitely use CNNs for feature extraction. I recommend you to take a look at this example.
I also recommend you to take a look at the following libraries. SK-LEARN, KERAS and PYTORCH. These libraries are very begginer friendly and they have amazing documentaries.
Best of luck.
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