Writing two papers on the same topic with the same data
It is entirely reasonable to produce more than one paper from the same project, focusing on different aspects of the the project.  Legitimately complicated projects often produce many papers worth of results: it only becomes unethical salami slicing if you're trying to "stretch" one paper into many.

The type of situation that you describe, however, is an extremely common circumstance for ending up with two papers, one focused on method (in this case, your algorithm) and the other focused on results (in this case, what has been learned from the biological data).  The two papers will necessarily be quite different: the methods paper must investigate questions of scaling, scope of applicability, etc., far beyond this particular dataset. Complementarily, the applications paper needs to consider underlying theories, alternative explanations, hypotheses, etc. with little bearing on how the data happens to have been analyzed.

From my own personal experience as both an author and a reviewer, I would recommend doing this in one of two ways:


If the two have similar audiences, you can co-submit two papers that reference one another to the same journal.  Explain this in the letters to the editor, and they will likely receive special handling that considers them as a linked unit, e.g., the same handling editor, possibly shared reviewers.
If the two have very different audiences, publish whichever is ready to go first, mentioning the issues of the other only briefly, then follow up with the other citing it.  This can be in either order, though if you're dealing with a high-impact biology journal, it may be wise to go with the biology paper first, since such publishers are sometimes touchy about "novelty" concerns.