Hacker News: comp_bio

New comment by comp_bio in "The first early human eggs from stem cells"

comp_bio — Wed, 01 Jul 2026 10:55:26 +0000

I think it’s important to remember that the process of selection acts directly on human traits. For example being exposed to high summer heat temperatures may eliminate some people who have unproductive sweat glands, or needing to run down your food may eliminate people who have a muscles that easily tire. Selection (largely) does not act on far removed traits like egg cell characteristics as a proxy of human traits like muscle performance because the genes that are used by egg cells are quite different than those used by muscle cells. So if you worry about some kind of human trait decline you should be much more worried that people have access to air conditioning and grocery stores.

New comment by comp_bio in "Gut bacteria from amphibians and reptiles achieve tumor elimination in mice"

comp_bio — Thu, 18 Dec 2025 03:44:07 +0000

This is a fascinating niche of evolutionary biology that I have worked in for a while. The short answer is that yes, as far as we can tell all organisms evolve increasingly more efficient replication machinery, however at some point the strength of selection is no longer powerful enough to overcome the strength of genetic drift and some degree of error rate persists. As far as we can tell it seems like population size governs where this balance ends up such that small populations have high mutation rates and large populations have reduced mutation rates. Michael Lynch coined the term drift barrier hypothesis to describe this phenomenon. https://pubmed.ncbi.nlm.nih.gov/23077252/

New comment by comp_bio in "Ask HN: Who wants to be hired? (August 2024)"

comp_bio — Fri, 02 Aug 2024 15:46:11 +0000

Location: Boston, Massachusetts, USA

Remote: Yes

Willing to relocate: No

Technologies: - Fields: Cancer Biology, Cancer Genetics, Population Genetics, Bioinformatics - Coding Languages: Python, R, Bash, Go, Rust - Computational Methods: Sequencing Analysis, Rare Variant Detection, GWAS, Sequence Alignment, Variant Calling, Mendelian Randomization, Polygenic Risk Scoring - Computational Tools: Scikit-learn, Numpy, Matplotlib, Pandas, SciPy, GATK, samtools, Seurat, Git/Github, Cluster Computing, Linux, Google Cloud Computing, AWS, Code Ocean, Random Forest, Deep Learning, K-Nearest Neighbor, Regression, Clustering, UKB, TOPMed, AllofUs, EHR - Wetlab Technologies: Amplicon Sequencing, Liquid Biopsies, NGS, sc-DNASeq, ddPCR, scRNA-Seq, CRISPR-Cas, System, Genome Editing, Cell Culture, ctDNA

Résumé/CV: https://github.com/liggettla/resume

Email: orb_05daring@icloud.com

LinkedIn: https://www.linkedin.com/in/lutheraliggett/

GitHub: https://github.com/liggettla/

I am a scientist with over 15 years of experience, principally with a focus on cancer genetics and computational biology. In most of my research positions I was responsible for both the wet-lab and the computational aspects of my projects. I have worked extensively on detecting rare somatic mutations of the hematopoietic system and used these mutations to model and understand the steps involved in the process of oncogenesis. In graduate school I built one of the most sensitive mutation detecting platforms in the world. I also have spent time translating my research to the clinic to inform physician decision making during cancer treatment. Additionally, I have worked to understand the role of mutation accumulation in the first human gene therapy clinical trials. In my most recent research I have been pursuing a population genetics approach to understand the evolution of somatic mutation rates in humans. Most recently I worked as a Senior Scientist in Computational Biology at a startup in Cambridge that leveraged mitochondrial mutations for lineage tracing of the hematopoietic tissue as a means of diagnosing early cancers.

Personal: I spend most of my spare time running, both in the woods, and when i'm late for meetings.