Just to be clear about how this is incredibly wrong, as clearly this poster has never read life science research, and it's very strange for such a blatantly misinformed comment to stick around on HN.
There are no biologists out there who are just looking for correlations, mistaking them for the real finding. Look through the life science papers in Nature, Science, Cell, PLoS Biology, etc. You will find people starting with a hypothesis, and running controlled, causal experiments, often with two or three different methodologies to establish non-correlational evidence. These are often based on initial observations that are correlational, but there is no publication where people are like "whoa, we found a correlation, our work is done!"
In contrast, there are some subfields where most of the work is correlational, and those are the fields where researchers are limited to analyzing data more than running experiements: epidemiology and bioinformatics. Now epidemiologists collect tons of data, but there's very little that they can do in noncorrelational analysis, because that's the nature of ethics and human life. But that doesn't mean that they don't try to invalidate their correlation-based hypotheses with experiments, it's just that they get to run very few of them. Bioinformatics is somewhat different, and in some ways is much more like a theoretical physics in that developing new methodology can be a publication-worth, even if there was no new data collected to validate the computational methodology.
In short, there's no truth at all to what return0 posted.
There are no biologists out there who are just looking for correlations, mistaking them for the real finding. Look through the life science papers in Nature, Science, Cell, PLoS Biology, etc. You will find people starting with a hypothesis, and running controlled, causal experiments, often with two or three different methodologies to establish non-correlational evidence. These are often based on initial observations that are correlational, but there is no publication where people are like "whoa, we found a correlation, our work is done!"
In contrast, there are some subfields where most of the work is correlational, and those are the fields where researchers are limited to analyzing data more than running experiements: epidemiology and bioinformatics. Now epidemiologists collect tons of data, but there's very little that they can do in noncorrelational analysis, because that's the nature of ethics and human life. But that doesn't mean that they don't try to invalidate their correlation-based hypotheses with experiments, it's just that they get to run very few of them. Bioinformatics is somewhat different, and in some ways is much more like a theoretical physics in that developing new methodology can be a publication-worth, even if there was no new data collected to validate the computational methodology.
In short, there's no truth at all to what return0 posted.