Category Archives: Bioinformatics

Mysteries of the scientific method

Scientific method can be understood as the following steps: formulating a hypothesis, designing an experiment, carrying out experiments, and drawing conclusions. Conclusions can feed into hypothesis formulation again, in order for a different (related or unrelated) hypothesis to be tested, and we have a cycle. This feedback can also take place via a general theory that […]

Historical noise? Simulation and essential/accidental history

Scientists and engineers around the world are, with varying degrees of success, racing to replicate biology and intelligence in computers. Computational biology is already simulating the nervous systems of entire organisms. Artificial intelligence seems to be able to replicate more tasks formerly thought to be the sole preserve of man each year. Many of the results […]

Exploring particularity

We have not yet succeeded in isolating an entity from other entities in such a way that what is isolated is utterly separate. Possibilities of mutual affect always remain. (I know of no way of shielding against the effects of gravity, for example.) Thus, it seems fair to think about every given entity as a particular […]

Science and non-repeatable events

Scientific method is fundamentally concerned with repeatable events. The phenomena that science captures most easily may be described using the following formula: once conditions A have been established, if B is done, then C happens.  This kind of science is a science of reactions, of the reactive. But what about a science of the active? Is […]

Small Tools for Bioinformatics

Pjotr Prins has published a Small Tools Manifesto for Bioinformatics, which is well worth a read for anyone who develops bioinformatics software. In essence it’s about increased adoption of the Unix design philosophy. I fully support the manifesto, which in many ways is reminiscent of the ideas that me and Gabriel Keeble-Gagnere presented in our […]