Post 10: Damn biologists, they ruined biology 🤬

Published: August 09, 2024

Historically, biologists have undermined new areas where biology expands and their new profiles. It is common to find molecular biologists belittling the work of bioinformaticians (bioinfos). “It’s just typing on a keyboard, and the results come out quickly, but they are merely hypotheses that can only be proven through experiments”. “The experiment tells you whether you’re right or wrong”. In reality, molecular biology is necessarily reductionist from its conception.

However, molecular biologists were also bullied in their time. Organismic biologists did not take molecular analyses seriously. It was unclear what was being purified or sequenced; the information obtained was often partial and/or messy, and the results derived from it had already been obtained with phenotypic information. Sometimes, they were absurd conclusions that compared apples to oranges. But that changed with the perfection of the technique, and now there are fewer organismic biologists and more molecular ones.

In the 70s-90s, molecular biologists established themselves as the dominant group, while foundational algorithms (like BLAST) consolidating bioinformatics as a field in its own right, along with others like biomathematics or systems biology. Since then, we have been undermined. For example, Sydney Brenner, a famous molecular biologists and Nobel laureate, threw shade at bioinfos, except for structural biologists whom he respected. Again, the technique improved, and since the 2010s, sequencing has become the paradigm of biological work. At this point, many bioinfos raised their voices:

“What matters are the questions you address, not the tools you use. Bioinfos are biologists who use a different tool,” said Markowetz.
“We imagine a world where molecular biologists are asked to perform computational validation just as we are asked todo experimental validation,” said Jafari and his colleagues.
“There is a data apocalypse, and computers will be necessary to advance in such murky territory. By 2039, biology and bioinformatics will be so intertwined that we won’t be able to distinguish them,” said Titus (paraphrased).

Now biology is expanding into a new area, AI, further promoting algorithmic approaches. We are starting to rely on new algorithms that surpass what we achieved based on biological principles. We are rediscovering the wheel just as molecular biologists and bioinfos did in their time. We accept that we cannot model all the variables of life, yet we still choose to approximate it, whether with biological principles or solely based on data, even if it is mechanistic—like modeling the cell cycle of yeast with 60 equations or predicting protein structures with million-dollar algorithms.

It is valuable to find scientists who, even knowing that this little venture is just starting, redirect their research efforts to give biology a new perspective. Ironically, those who only offer sound and incisive critiques of this venture are often the same ones who do not get their hands dirty to fix it. Meanwhile, those who plunge into the sea without knowing how to swim sometimes drown along the way, though occasionally they find a promising path where new ideas can flourish.

Exploring new paradigms that are completely different from those already in use seems to me an act of humility. However, it seems we are doomed to repeat our history. It is going to happen again.

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