Cheminformatics – the New World for TCS?

A few weeks back Aaron Sterling posted a review of the Handbook of Cheminformatics Algorithms (in which I have a chapter). Aaron notes … my goal for the project changed from just a review of a book, to an attempt to build a bridge between theoretical computer science and computational chemistry … The review/bridging was […]

Are Bioinformatics Results Too Good To Be True?

I came across an interesting┬ápaper 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”. The former phenomenon is characterized by researchers identifying datasets on which their method works better […]

Drug Discovery Trends In and From the Literature

I came across a recent paper by Agarwal and Searls which describes a detailed bibliometric analysis of the scientific literature to identify and characterize specific research topics that appear to be drivers for drug discovery – i.e., research areas/topics in life sciences that exhibit significant activity and thus might be fruitful for drug discovery efforts. […]

Squeezing Journal Space?

An article by Steven Bachrach in the Journal of Cheminformatics has an excellent disscusion on Open Access journals. He notes that one of the problems with current scientific publishing is the plethora of journals. He also points out the huge amount of publications being generated. He succinctly states it as We simply publish way too […]

The Quest for Universal Descriptors – Not There Yet

A major component of QSAR modeling is the choice of molecular descriptors that are used in a model. The literature is replete with descriptors and there’s lots of software (commercial and open source) to calculate them. There are many issues related to molecules descriptors, (such as many descriptors being correlated and so on) but I […]