Its Science Jim, but not as we know it

The discussion on publishing models, the problems of peer-review and the lack of reproducibility in science took a new turn last week when Nature Publishing Group stiffened their policies on data integrity.
This is a great move and motivated by concerns over the reproducibility of published work. Indeed I have heard from industry figures as high as “50% of biomedical papers are not reproducible”. Examples include a study by Amgen, which showed that 47 of 53 papers they examined failed the reproducibility test and one by Bayer, where 43 of 47 papers were found not to be reproducible.
The problem is not restricted to clinical science. So a simple question is why? After all, reproducibility is meant to lie at the heart of science. A compelling article in the New York Times, based on an interview with Stapel, the fraudulent Dutch psychologist, provides some key insights. The article, entitled “The mind of a con man” by Yudhijit Bhattacharjee should be compulsory reading.
What follows is not an attempt to place blame, but to see what lessons we can learn. I have selected a few excerpts.

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“Analysis of the FGFR Signalling Network with Heparin as Co-Receptor”

Ruoyan’s paper on “Analysis of the FGFR Signalling Network with Heparin as Co-Receptor: Evidence for the expansion of the core FGFR signaling network” is out.

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In Defence of REF

I never thought I would write a post with this title and, after last week, it is even more surprising. Nonetheless, I am a modest fan of REF and this post sets out why.

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One future of science publishing

The rapid change in science communication is leading to multithreaded discussions on peer review (just one example of many, Philip Moriarty’s recent posting at the IOP) and models for journals. The latter discussions are backed by journals following new models for both the business and the reviewing side; PeerJ is the most radical and recent example here. I was recently asked to participate in a survey by Langmuir/ACS, which I duly completed. This post summarises my reaction to the survey and some of my post survey thoughts. The questions revolved around peer review (blind, double blind, open and so on) from the point of view of the reviewer and the author. There was also a box to fill in with additional comments. What I wrote in that box is:

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Sue, Grabbit and Runne

Further legal attempts to silence scientific discourse, Retraction Watch has been threatened by a law firm acting on behalf of Bharat Aggarwal.

This is getting ridiculous. Take a look at the facts.

Anil Potti, disgraced medical researcher at Duke was running ‘trials” that put lives at risk. Statements of fact at Retraction Watch regarding the official investigations into Anil Potti resulted in a false DMCA take down notice being issued to Retraction Watch (posts here and here with links).

Bharat Aggarwal’s work is under official investigation and some of the many papers highlighted on varous blogs (more about these below) have been retracted and these retractions have been featured on Retraction Watch.

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Scientific publishing – which way forward?

As I spend time wading through REF submissions for our Institute, I harbour ever darker thoughts on evaluating papers and journals. Why has the “system” become so bogged down in a crazy recursive logic that I cannot do something interesting? Research and Teaching become almost displacement activities.
Crazy.

I will post at some length on the subject in the future, meanwhile, as much a reminder to me as anything else, an excellent post by Michael Eisen on Scholarly Publishing, which is well worth reading.

Also, a new journal. No, not one filling a perceived vacuum, filled by Nature, but a New Journal. Working along somewhat different lines to the PLOS family, including the cost: PeerJ.

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Fraud in research: Individuals and Systems

A great update on a post by Paul Hutchings

Fraud in research: Individuals and Systems.

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Differential responses need new mathematics

I’m looking for an explanation for these data. Can anyone figure out how 1-3 below add up? I don’t think the answer can be “science”, “evidence based decision making” or “square root of 36”, but I am happy to be corrected.

1. A subject of a previous posting (and here), an image from a Nature Materials paper is re-used for a different experiment in a subsequent PNAS article. This warranted a correction.

2. Recently posted on Retraction Watch, a rapid retraction in PNAS, after an error was pointed out by a Nobel Laureate

3. Another recent posting on Retraction Watch on a retraction at Translational Research. This retraction was preceded by a correction, where the re-used data were replaced by other data. The correction states “figures 4A∼4I were incorrect”, without any allusion to the re-use of data. Only after an investigation by Nagoya City University and the University requesting a retraction did the journal pull the paper.

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