But this does not change the fact that we strongly disagree with the fundamental argument put forward by Clark et al., which is that the genomic area corresponding to transcripts is more important than their relative abundance. This viewpoint makes little sense to us. Given the various sources of extraneous sequence reads, both biological and laboratory-derived (see below), it is expected that with sufficient sequencing depth the entire genome would eventually be encompassed by reads. Our statement that “the genome is not as not as pervasively transcribed as previously reported” stems from the fact that our observations relate to the relative quantity of material detected.
Of course, some rare transcripts (and/or rare transcription) are functional, and low-level transcription may also provide a pool of material for evolutionary tinkering. But given that known mechanisms—in particular, imperfections in termination (see below)—can explain the presence of low-level random (and many non-random) transcripts, we believe the burden of proof is to show that such transcripts are indeed functional, rather than to disprove their putative functionality.
Tag: Scientific Process
What makes a paper bad instead of just wrong
The editor of the journal Remote Sensing just resigned over the fact that his journal published a paper that should never have been published. Real Climate explains what that means – being controversial or eventually shown wrong is *not* an indication that a paper shouldn’t have been published. This is what makes a paper bad:
But what makes a paper ‘bad’ though? It is certainly not a paper that simply comes to a conclusion that is controversial or that goes against the mainstream, and it isn’t that the paper’s conclusions are unethical or immoral. Instead, a ‘bad’ paper is one that fails to acknowledge or deal with prior work, or that makes substantive errors in the analysis, or that draws conclusions that do not logically follow from the results, or that fails to deal fairly with alternative explanations (or all of the above). Of course, papers can be mistaken or come to invalid conclusions for many innocent reasons and that doesn’t necessarily make them ‘bad’ in this sense.
Winning science by attrition is boring
Nature has an interesting piece on the 24/7 lab:
It’s just about midnight on a hot Friday night in July, Enrique Iglesias’ ‘ Dirty Dancer ‘ is on the radio, and 26-year-old graduate student Sagar Shah is starting to look winded. The problem, he says, is not how late it is, or even that he has spent the past three hours working in a cramped sterile cell-culture hood. The problem is that the routine cell-culture maintenance he is doing, bathing his collection of rare human tumour cells with fresh medium, produces no data. And a lack of data, says Sagar, makes him “hungry” for it.
The piece goes on to talk about one of those high-intensity, work all weekends and holidays labs. That lab, and many like it, certainly crank out papers, but they are basically factories. Continue reading “Winning science by attrition is boring”
Science musings
What biologists need to do more of:
A major goal in all sciences is to be able to explain large-scale phenomena as consequences of the interactions of small-scale components. This is what drives me to study what I’m studying – in my case, the large scale-phenomena are patterns of gene expression, and the small-scale components are transcription factors and DNA binding sites.
Biologists do a lot of measuring of large-scale phenomena, via genomics or classical genetic phenotying. Biologists also spend a lot of time discovering what the small-scale components and interactions are. But they don’t really spend enough effort trying to understand how it is that large-scale phenomena are consequences of the interactions of small-scale components.
Just to be clear: your typical blob-and-arrow pathway diagram featured in Figure 7 of nearly every Cell paper (Fred Cross calls these ‘Figure 7 models’) is not the answer to this question, because it is essentially impossible, in nearly all cases, to predict the large-scale behavior just by looking over one of those diagrams.
I can’t decide whether Quantum Man is the best Feynman biography
Along with Gleick’s outstanding biography, Lawrence Krauss’ Quantum Man is now one of the essential Feynman books. While Gleick’s book is biography at its finest, Krauss’s is the best picture of Feynman’s position within the physics community, which is obviously something that could only be written by a serious physicist, like Krauss. Krauss, better than anyone else, has explained why Feynman was seen as a great scientist by physicists themselves, who are not the types to be swayed by the anecdotes that made Feynman popular with the public. Feynman was a great public communicator, and purposely developed a particular public persona, but his physics accomplishments were completely equal to his fame, as Krauss makes clear. I learned more about Feynman’s style of doing science (including its weaknesses of insularity) from this book than from any other.
So here’s how I would categorize the existing Feynman biographies: Continue reading “I can’t decide whether Quantum Man is the best Feynman biography”
The Finch and Pea 