Why do computer science students working in computational biology domain need to give biological validation for their prediction? I am in my 3rd year of PhD. I am doing my PhD on Computational Biology, with a background of purely Computer Science. Since I am under pressure to publish 4 more journal papers, apart from my review, I am always in a hurry to do the same. What I have noticed for this field is that if I predict something, I need to provide biological validation for my result. Why so? Is biological validation not the work of biologists? How can a computer science student provide biological validation for his/her prediction? Isn't our job just to predict? Why do the journals want biological validation for the results? I did a prediction job, where I predicted some proteins to do a particular function. I communicated it to the Molecular BioSystems Journal. They rejected it saying I have no biological validation. If biologists are the one with the final say, then what point do we have in working in this domain? Whatever we predict would be questioned.
I am always in a hurry to do the same. What I have noticed for this
  field is that if I predict something, I need to provide biological
  validation for my result. Why so?


Because this is how one knows if your results are correct and useful. A prediction is nothing if it hasn't been evaluated. The field is littered with predictions that turn out to be nonsense, only hold up under very narrow circumstances, etc.


  Is biological validation not the work of biologists?


No more than it would be if a biologist said "I just developed this algorithm, proving it's correct is the work of a computer scientist."

Beyond that, there's no reason for them to do so. "I've made an arbitrary prediction, anyone want to validate it?" is going to be met with a resounding "No" - the biologists have their own work to do.


  How can a computer science student provide biological validation for
  his/her prediction? Isn't our job just to predict?


No, it's your job to provide useful results. Validated predictions are useful. Just predictions are not.

As people have noted, there are a number of ways to validate a prediction. Existing data, or even simulated data based on known biological patterns, might be sufficient. If no such data exists, it's time to find a collaborator.


  Why do the journals want biological validation for the results?


Because anything else is just speculation.


  I did a prediction job, where I predicted some proteins to do a
  particular function. I communicated it to the Molecular BioSystems
  Journal. They rejected it saying I have no biological validation. If
  biologists are the one with the final say, then what point do we have
  in working in this domain? Whatever we predict would be questioned.


Do you know that it was rejected by a biologist? There's a number of computer scientists I know who would have rejected such a paper for having no biological validation. Beyond that, your "point" in working in the field is to generate those predictions and evaluate their correctness. The latter part is also an aspect of good computational biology.