Trust in Bioinformatics

Rajarshi summarizes a recent paper in Bioinformatics about trusting
Bioinformatics results:

…paper by Ann Boulesteix where she discusses the problem of false positive results being reported in the bioinformatics literature. She highlights two underlying phenomena that lead to this issue – “fishing for significance” and “publication bias.”
As I have been reading the microarray literature recently to help me with RNAi screening data, I have seen  the problem firsthand. There are hundreds of papers on normalization techniques and gene selection methods. And each one claims to be better than the others. But in most cases, the improvements seem incremental. Is the difference really significant? It?s not always clear.

The second part is very relevant to the development of good open source tools. We need our scientific rewards system to encourage building on prior work.

Related to trust, Clay Shirky has a nice post regarding algorithmic
authority. It covers the point at which you trust the results from
an algorithm to be correct, relating it to our trust systems in


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