TU : Why Are Numbers Key in Modern Biology? 🧬📊

𝘓𝘢 𝘣𝘪𝘰𝘭𝘰𝘨𝘪𝘦 𝘢̀ 𝘭’𝘦́𝘱𝘳𝘦𝘶𝘷𝘦 𝘥𝘦𝘴 𝘤𝘩𝘪𝘧𝘧𝘳𝘦𝘴 : 𝘔𝘦𝘴𝘶𝘳𝘦𝘳, 𝘗𝘳𝘦́𝘥𝘪𝘳𝘦 𝘦𝘵 𝘋𝘦́𝘴𝘪𝘨𝘯𝘦𝘳 by Prof. Cherine Bechara & Dr. Luca Ciandrini

At first glance, biology might seem like a qualitative science, full of observations, descriptions, and complex living systems that appear difficult to quantify.

However, over the past few decades, it has increasingly turned to quantitative approaches, revealing that numbers are not merely tools for measurement, but are essential for understanding, predicting, and designing biological systems.

📊 𝗗𝗲 𝗹’𝗼𝗯𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝗼𝗻 𝗮̀ 𝗹𝗮 𝗾𝘂𝗮𝗻𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻

This shift is driven by technological advances and the culture of data. The dramatic drop in the costs of DNA sequencing and synthesis has made biology not only measurable but also programmable. Today, we can read, write, and even design biological systems using digital models—an idea that was unimaginable just a generation ago.

But this capability comes with a new challenge: a veritable deluge of data. Today, biologists are generating enormous amounts of information—from genomes to imaging data—faster than we can analyze it effectively. The question is no longer “How do we obtain data?” but rather “What do we do with all this data?”

🔢 𝗗𝗲 𝗹𝗮 𝗱𝗼𝗻𝗻𝗲́𝗲 𝗮̀ 𝗹𝗮 𝗰𝗼𝗺𝗽𝗿𝗲́𝗵𝗲𝗻𝘀𝗶𝗼𝗻 : 𝗹𝗲 𝗿𝗼̂𝗹𝗲 𝗱𝗲𝘀 𝗰𝗵𝗶𝗳𝗳𝗿𝗲𝘀

This is where numbers—in the form of statistics, estimates, and models—become the cornerstone of modern biology. According to the FAIR principles (Findable, Accessible, Interoperable, Reusable), scientific data must not only be produced but also reused to generate new knowledge.

To make sense of this flood of data, we explored “Fermi problems”—estimation exercises that teach us to think quantitatively, even when information is limited. This approach helps develop an intuition for the scales and dynamics of biological systems: How many cells are in the human body? How quickly can a bacterium develop resistance? Etc.

𝗩𝗼𝗶𝗿 (𝗲𝘁 𝗿𝗮𝘁𝗲𝗿) 𝗹𝗲𝘀 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 🔀

Numbers help reveal hidden patterns in data, while also showing just how easy it is to miss the big picture. In class, we discussed selective attention and inattentional blindness—cognitive biases that influence how researchers interpret results. Recognizing these biases is essential for designing fair and unbiased experiments and surveys.

✅ 𝗣𝗼𝘂𝗿𝗾𝘂𝗼𝗶 𝗰𝗲 𝗰𝗼𝘂𝗿𝘀 𝗲𝘀𝘁-𝗶𝗹 𝗶𝗻𝗱𝗶𝘀𝗽𝗲𝗻𝘀𝗮𝗯𝗹𝗲 ?

𝘓𝘢 𝘣𝘪𝘰𝘭𝘰𝘨𝘪𝘦 𝘢̀ 𝘭’𝘦́𝘱𝘳𝘦𝘶𝘷𝘦 𝘥𝘦𝘴 𝘤𝘩𝘪𝘧𝘧𝘳𝘦𝘴 invites students to view living systems differently, no longer as disordered and unpredictable phenomena, but as measurable, modelable, and conceivable systems governed by quantitative principles.

Learning to measure, predict, and design means equipping ourselves to cross the next frontier in biological discovery.