Question: A bioinformatics expert analyzes 9 gene sequences, 5 of which are mutated. If 3 sequences are chosen at random, what is the probability that at least 1 is mutated?

Mon, 04 May 2026 18:00:52 +0000

**Understanding Genetic Probability: What Science Says About Mutated Gene Sequences** When breakthroughs in genetic analysis begin trending online, users naturally ask: What’s the real likelihood behind genetic patterns? A recent question reflects growing interest: A bioinformatics expert analyzes 9 gene sequences, 5 of which are mutated. If 3 sequences are selected at random, what’s the chance at least one is mutated? Far from niche trivia, this type of probability analysis underpins critical discoveries in medicine, evolutionary research, and personalized health. Understanding it builds a foundation for interpreting complex genomic data—especially relevant as predictive health tools gain US traction. **The Science of Genetic Selection: Why This Question Sparks Curiosity**
The question arises amid increasing public awareness of genetic testing and precision medicine. With over 9 million gene sequences being studied annually in the U.S., analyzing mutation patterns within samples has become a core tool for identifying disease risks and evolutionary markers. The setup—9 sequences, 5 mutated—sets the stage for a statistical analysis that mirrors real-world lab scenarios. People are drawn not to sensational claims, but to a grounded, logical calculation that reveals underlying genetic dynamics. **How This Genetic Probability Problem Really Works**
Rather than guess, the question invites a methodical probability calculation. With 9 total sequences and 5 mutated, selecting 3 at random means sampling without replacement. The goal is to compute the chance at least one selected sequence is mutated—a question that highlights complementary probability: it’s often easier to calculate the chance of zero mutations and subtract from 1. This approach applies broadly in genetic studies and offers insight into sample selection reliability.