You Can’t Get Back Your Time

Time. You can’t get it back.

That truth, once spoken through a dream, now echoes like a signal in the noise, simple, undeniable, and too often ignored or deliberately overlooked.

In science, especially in bioinformatics, we deal with time in data: evolutionary timelines, molecular clocks, progression of diseases, lifespan analyses. But rarely do we apply the same analytical scrutiny to our own timeline. Life is short. Circumstance, I’ve learned, is more often a choice than we admit. Movement or stagnation isn’t imposed, it’s a decision, made in moments we often pretend are out of our control.

So who, in the end, will be accountable for the unlived time?

For the chapters that remained unwritten not out of impossibility, but fear? On the deathbed of complacency, the question isn't just scientific, it's personal. What data did we choose to ignore? What experiment did we refuse to run?

"You can’t take back your time." Those words aren’t just philosophical, they're actionable. They’re a variable to optimize against. And with them in mind, I no longer see regret when looking back. Instead, I see the illuminated potential ahead. Gratitude not for what has passed, but for what is still possible. For the unexplored connections, the collaborations not yet sparked, the insights not yet derived.

What if we stopped living as if time were linear, fixed, and human-defined? What if we allowed the spirit to step outside the dataset? What could we discover when fear no longer determines the boundaries of our inquiry?

Imagine progress not defined by certainty but by iteration: a try, a fall, a rise. An unpredictable outcome, a dataset filled with anomalies that become the next breakthrough. The real power, perhaps, lies not in controlling the results but in having the courage to run the experiment at all.

That’s where growth lives. Not in the known, but in the attempt. And every attempt, successful or not, opens another door. A higher version of self, a more informed, aware, and evolved you, emerges.

This is not just philosophy. This is a call to action. A hypothesis worth testing: That living fully is the most precise algorithm we’ll ever write.