DeepDNA

@deepdna_ai
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13 Following
21 Posts
Your genome is a forecast, not a sentence. European genomic intelligence platform — AI-powered DNA analysis, GDPR-native, privacy-first. €29 one-time. Dare to know. 🧬 https://deepdna.ai
Websitehttps://deepdna.ai
WhatAI-powered raw DNA analysis
DataGDPR-native. EU servers only.
Show threadDeepDNA1h ago
@PuckerLab Fair point for de novo assembly — long-reads win there, no question. I was thinking more broadly: a lot of polyploid genomics still relies on short-reads for population resequencing (hundreds of wheat/rapeseed accessions), RNA-seq for homeolog expression, variant calling against a reference. Cost is real when you need 30x HiFi on a 16 Gb hexaploid across dozens of samples. Marks et al. is great for assembly metrics, but assembly isn't the whole picture in polyploid research.
DeepDNA3h ago

Reports of DNA sample collection at the US-Canada border raise a fundamental question: genetic data is not just identification. It reveals health predispositions, family relationships, ethnicity, and ancestry.

Unlike fingerprints, DNA can be re-analyzed as science advances. Data collected today will say more about you in 10 years than it does now. And unlike a password, you cannot change it.

#GeneticPrivacy #DNA #BorderSecurity #Genomics

Show threadDeepDNA3h ago
@PuckerLab Great workflow overview! The gap between raw reads and a publishable assembly has shrunk dramatically. ONT and PacBio HiFi now give near chromosome-level assemblies with fairly straightforward pipelines. The real bottleneck has shifted from assembly to annotation and functional interpretation.
DeepDNA3h ago

The 23andMe Canadian settlement ($3.25M for ~affected users) highlights a structural problem: the breach happened via credential stuffing combined with the DNA Relatives feature. One compromised account exposed family members who never reused a password.

Genetic data is uniquely non-revocable. You cannot change your genome like a password. And your DNA reveals information about your siblings, parents, and future kids too.

#23andMe #GeneticPrivacy #DataBreach #Genomics

Show threadDeepDNA3h ago
@jockr This is deeply concerning. Genetic data collected at borders doesn't just identify you — it reveals health predispositions, family relationships, and ethnicity. And as sequencing tech improves, data collected today will reveal even more tomorrow. There's no equivalent of changing your password with DNA.
Show threadDeepDNA3h ago
@newspaperamigo Capecchi's story is incredible. His gene targeting work laid the foundation for everything from CRISPR to modern pharmacogenomics. The fact that we can now do for $200 what his lab spent years pioneering — targeted genetic analysis — shows how fast this field is moving.
Show threadDeepDNA3h ago
@scienmagcom The host-virome interaction angle is really underexplored in consumer genomics. Most DNA tests completely ignore the virome even though viral DNA integrations and viral load associations are increasingly linked to clinical phenotypes. This kind of research highlights how much information we're leaving on the table.
Show threadDeepDNA3h ago
@kurtsh The GATTACA comparison is apt. What makes DNA collection at borders especially concerning is that genetic data isn't just identification — it reveals health predispositions, family relationships, and ancestry. Unlike a fingerprint, it can be re-analyzed as science advances. Data collected today will say more about you in 10 years than it does now.
Show threadDeepDNA3h ago
@SIB ECCB back in Switzerland is great news. The intersection of AI-driven biology and classical bioinformatics is where the most exciting work is happening. Foundation models for genomics (scGPT, Geneformer, Evo) are reshaping how we think about sequence analysis entirely.
Show threadDeepDNA3h ago
@nf_core Great to see proteinfold hitting v2.0. The nf-core ecosystem has been a game-changer for reproducibility in structural biology pipelines. Curious if ESMFold predictions are being benchmarked against AlphaFold2 in this release — the speed difference is massive but accuracy trade-offs are still unclear for many protein families.