The hottest Bioinformatics Substack posts right now

And their main takeaways
Category
Top Technology Topics

A Visual Guide to DNA Sequencing

Asimov Press • 851 implied HN points • 26 Feb 26
🔬 Science Bioinformatics
  1. DNA sequencing has moved from slow, radioactive lab work to fast, automated machines, causing sequencing costs and turnaround times to fall dramatically.
  2. Different technologies make trade-offs: some (like Illumina) give very accurate short reads, others (like PacBio and nanopore) produce long reads useful for repetitive or complex regions, and nanopore adds portability and real-time reading.
  3. These advances have revolutionized biology and medicine by enabling large-scale genome projects, clinical genetic testing, ancient DNA and metagenomics studies, and ongoing efforts to make whole-genome sequencing even cheaper and more widely available.

Future Of Protein Sequencing

ASeq Newsletter • 29 implied HN points • 11 Mar 26
🔬 Science Bioinformatics
  1. Protein sequencing is much harder than DNA sequencing and has fewer broad, foundational applications, making commercial success expensive and difficult.
  2. Without big academic champions and large research projects to drive adoption, companies are forced into niche revenue paths that pull development away from a general-purpose sequencing platform.
  3. There are realistic niche opportunities like biopharma QA/QC and sensitive biomarker detection, but turning protein sequencing into a widely used tool will require sustained funding, risk tolerance, and strong research adopters.

BGI Nanopore Peptide Profiling

ASeq Newsletter • 21 implied HN points • 10 Mar 26
🔬 Science Bioinformatics
  1. BGI demonstrated a scaled-up method for classifying peptides with nanopores, showing the approach works beyond small proofs of concept.
  2. They attach DNA handles to peptide ends so peptides can be threaded and paced through a nanopore using existing DNA sequencing control.
  3. The study revealed more technical detail about BGI’s nanopore platform, indicating it could be adapted for larger-scale protein or peptide analysis.

More Roche SBX Workflow Thoughts

ASeq Newsletter • 21 implied HN points • 05 Mar 26
🔬 Science Bioinformatics
  1. There are two Axelios workflows being compared: SBX-D is a duplex, multi-day protocol around 19 hours, while SBX-Fast completes in roughly 3.5 hours.
  2. Collected run data were used to directly compare SBX-D and SBX-Fast to show their relative throughput and performance differences.
  3. The comparison highlights trade-offs between speed and duplex capability, so choosing a workflow depends on whether higher throughput or shorter turnaround time is more important.

A Few More Roche SBX Chip Notes

ASeq Newsletter • 21 implied HN points • 03 Mar 26
🔬 Science Bioinformatics
  1. More technical details and small updates about the Roche SBX chip are still being discussed.
  2. TruPath is noted as interesting but not very exciting here, partly because it’s already been covered elsewhere.
  3. The write-up is behind a paywall and requires a paid subscription or sign-in to access.
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DNA And Protein Sequencing Companies

ASeq Newsletter • 58 implied HN points • 02 Feb 26
🔬 Science Bioinformatics
  1. Protein sequencing is becoming a growing startup space, with many companies now working to make protein readouts practical.
  2. Two main technical routes dominate—optical methods and nanopore-based sequencing—while a smaller set of firms pursue other novel approaches, and multiple companies are active in each category.
  3. An updated directory of DNA sequencing companies is maintained, and contributors are invited to share additional firms to keep the list current.

Why Are We So Excited About Roche?

ASeq Newsletter • 21 implied HN points • 23 Feb 26
🔬 Science Bioinformatics
  1. Roche’s new Axelios single-molecule sequencer appears to be a real engineering breakthrough that can match or beat Illumina on key metrics like read length, speed, throughput, and accuracy.
  2. Because Roche is large, well-funded, and running global pilots, it can aggressively compete on price and scale, potentially grabbing significant market share if reuse and pricing work out.
  3. Significant uncertainty remains due to Roche’s mixed history, pricing and purchasing-cycle risks, and execution challenges, so excellent technology doesn’t guarantee immediate market disruption.

scBench: Can AI Agents Analyze Real-World Single-Cell Data?

LatchBio • 33 implied HN points • 06 Feb 26
🔬 Science Bioinformatics
  1. scBench is a realistic benchmark of 394 verifiable single-cell RNA‑seq problems spanning six sequencing platforms and seven task types, using real data snapshots and deterministic graders to mimic the decisions bioinformaticians make.
  2. Frontier models do better on scRNA‑seq than on spatial data but are still unreliable overall: the best model scores about 52.8% and tasks requiring scientific judgment (cell typing, clustering, differential expression) are the hardest while procedural steps (normalization, QC) are easiest.
  3. Which sequencing platform the data come from matters as much or more than model choice—platforms drive large accuracy swings—so trustworthy automation will require platform‑aware tooling, better harness design, and more representative training data.

Automating Biology

A Biologist's Guide to Life • 29 implied HN points • 26 Jan 26
🔬 Science Bioinformatics
  1. Living systems are layers of metabolic machines — from genes and proteins to cells, tissues, and organisms — that act like modular, self-replicating components we can study and engineer.
  2. Physical automation (robotic labs, cloud labs) and digital automation (AI-driven biodesign and structure prediction) can make experiments much cheaper, higher-throughput, and faster, enabling far more data and quicker innovation.
  3. Widespread automation is limited by trust, data security, and the need for flexibility as methods evolve, so modular, autonomous lab systems and careful governance are needed to realize its promise.

P2 Solo Alternatives (But Probably Not For You)

ASeq Newsletter • 21 implied HN points • 29 Jan 26
đź•ą Technology Bioinformatics
  1. Several companies now offer compact, high‑throughput nanopore sequencers (Qitan Q‑P2, MGI CycloneSeq/G100‑ER, PolySeq X2, Meilitech), but most models are currently sold mainly in China or Russia and are hard to obtain elsewhere.
  2. MGI's CycloneSeq is the most likely near‑term global alternative, yet it faces legal/IP disputes, possible sales restrictions and tariffs, unclear pricing, and reports of lower data quality compared with established platforms.
  3. The growing number of competitors shows nanopore know‑how isn't exclusive to one company, so competing platforms will probably improve and become more widely available over time.

agent.bio

LatchBio • 63 implied HN points • 09 Dec 25
🔬 Science Bioinformatics
  1. An interactive sandbox hosts natural-language agents tailored to five major spatial biology platforms (Takara Seeker, Vizgen MERFISH, AtlasXOmics DBiT-seq, 10X Xenium, and 10X Visium) so scientists can run end-to-end spatial analyses.
  2. Agents operate in two modes—"proactive" for automated runs and "step-by-step" for frequent check-ins—and users should prefer step-by-step for important work because the sandboxes were built for specific datasets and may not generalize perfectly.
  3. Video demos show these agents can ingest raw outputs, run QC, clustering, differential tests, and annotate spatial features across diverse biological problems, and the roadmap focuses on benchmarks, purpose-built infrastructure, and tech-specific heuristics to make agents reliable for scientific decisions.

SpatialBench: Can Agents Analyze Real-World Spatial Biology Data?

LatchBio • 41 implied HN points • 26 Dec 25
🔬 Science Bioinformatics
  1. SpatialBench is a realistic suite of 146 verifiable spatial biology problems across five platforms and seven task types that recreates real analyst workspaces using snapshots of data and images.
  2. Current agent models perform poorly overall (roughly 20–38% accuracy) and vary widely by task and platform, and the choice of execution harness or wrapper can change outcomes as much as changing the base model.
  3. Inspecting agent trajectories reveals clear failure modes and productive strategies, showing that detailed traces help explain performance and that benchmarks like this are a practical first step toward engineering agents that can reliably automate spatial biology analysis.

ASeq, 200 Posts in 2025. Subscription Discounts.

ASeq Newsletter • 7 implied HN points • 29 Dec 25
🔬 Science Bioinformatics
  1. Two hundred posts were published in 2025 and there’s an archive of over 500 posts available behind a subscription; access is $20 per month.
  2. Two limited-time annual discounts are being offered: 25% off standard annual subscriptions and 50% off annual subscriptions for educational users.
  3. The newsletter delivers focused coverage of DNA sequencing, life-science tools, diagnostics, and industry news, and relies on subscription revenue to sustain a niche audience with relatively low conversion rates.

Dear Shambolic Oligarchs: Here’s What I Did This Week

Viruses Must Die • 96 implied HN points • 25 Feb 25
🔬 Science Bioinformatics
  1. There's a plan to create a vaccine for chickens using yeast to help them fight bird flu. This involves some complex science but aims to protect poultry.
  2. Efforts are underway to upload massive amounts of viral data to a federal cloud, making it easier for scientists to access crucial information. However, workplace issues are causing worries about delays.
  3. A colleague discovered a cancer treatment but was let go during a staff change, which highlights the challenges faced by dedicated scientists and the impact of workplace stress on their work.

A Sneak Peak into New Spatial Analysis Tools

LatchBio • 23 implied HN points • 23 Jul 25
đź•ą Technology Bioinformatics
  1. There's an upcoming webinar on July 29, 2025, focused on a new tool for analyzing spatial datasets. It's hosted by Takara Bio and LatchBio.
  2. The webinar will showcase various methods like image alignment and gene expression analysis, so attendees can learn about these important topics.
  3. Participants will get to see live demonstrations of how to use these new analysis methods, which can be very helpful for anyone working with the Seeker™ and Trekker™ datasets.

An AWS For Sequencing?

ASeq Newsletter • 58 implied HN points • 16 Nov 24
đź•ą Technology Bioinformatics
  1. Bioinformatics companies often struggle to succeed on their own, but some are finding unique ways to add value by providing analysis of sequencing data from external service providers.
  2. Just like how companies can use AWS for their server needs, the idea is to create an AWS-like platform specifically for DNA sequencing, making services easier and more accessible.
  3. Building a platform for sequencing could lower barriers for businesses and encourage new applications in the field, opening up more opportunities for innovation.

LatchBio

axialdaily • 19 implied HN points • 23 Mar 23
đź•ą Technology Bioinformatics
  1. Axial invests in early-stage life sciences companies and supports rare inventors.
  2. LatchBio offers a platform for scientists to store, process, and visualize data and is hiring.
  3. Users can run different workflows and access popular tools in life sciences through Latch.

Codon Digest: GPT-4 Controls a Robot

Asimov Press • 90 implied HN points • 16 Apr 23
🔬 Science Bioinformatics
  1. GPT-4 controlled a lab robot to conduct chemical reactions, showcasing the potential of using natural language to automate experiments.
  2. Skin microbes were engineered to activate the immune system to fight tumors when applied to the skin, offering a novel cancer treatment approach.
  3. Tobacco plants were genetically modified to produce moth sex pheromones, providing a natural way to repel male moths from crops and protect them.

Keeping up with the State-of-the-Art in TechBio

Kesav’s Lab • 12 implied HN points • 21 Feb 25
đź•ą Technology Bioinformatics
  1. The Nobel Prize in Chemistry was awarded for breakthroughs in understanding protein structures, which can lead to better medicines and solutions to major health challenges.
  2. There’s a growing community focused on TechBio, which merges technology and biology. Events like meetups can help people learn and connect over important topics.
  3. Staying informed about the latest in TechBio is important, and contributing to community newsletters helps track new tools and research developments.

4 Reads Per Cluster! Simultaneously Paired End-Sequencing!

ASeq Newsletter • 36 implied HN points • 31 Jan 24
🔬 Science Bioinformatics
  1. Illumina has a method to potentially double their instruments' throughput, but it may come with a slight decrease in accuracy.
  2. By simultaneously reading both the forward and reverse strands, Illumina can achieve four reads per cluster, doubling the throughput.
  3. Implementing the simultaneous paired-end sequencing approach may be challenging without sacrificing accuracy, but it opens up opportunities for increased throughput in the future.

Functional protein mining with conformal guarantees

Axial • 14 implied HN points • 28 Nov 24
🔬 Science Bioinformatics
  1. A new method is developed for predicting protein functions using something called conformal prediction. This makes the predictions more reliable and provides a clear way to understand risks when selecting proteins.
  2. The approach helps in annotating genes and predicting enzyme functions more accurately without needing new training models. This is great for speeding up research in life sciences.
  3. It also offers a smart way to reduce the number of proteins needing full analysis, making the process quicker and cheaper while still keeping good accuracy.

Birth of protein folds and functions in the virome

Axial • 14 implied HN points • 24 Nov 24
🔬 Science Bioinformatics
  1. A lot of viral proteins have unique structures, showing there's still much to discover in the viral world. More than half of these proteins are structurally different from anything we've seen before.
  2. Some viral proteins are surprisingly similar to human proteins, which allows viruses to trick our cells. This understanding could lead to new ways to combat viral infections.
  3. Using advanced techniques to study protein structures is really powerful. It can reveal function and relationships that traditional methods might miss, helping us understand viruses better.

How to Engineer Therapeutic AAVs

LatchBio • 15 implied HN points • 14 Nov 24
🔬 Science Bioinformatics
  1. Adeno-associated viruses (AAVs) are used for gene therapy because they can deliver therapeutic genes safely without causing disease in humans. They're like little delivery trucks that send important genetic information to specific parts of the body.
  2. Dyno Therapeutics created a new version of AAV called Dyno bCap1, which is much better at getting to the brain and avoiding the liver, showcasing how engineering can significantly improve these therapies.
  3. By using machine learning, scientists can design better AAVs by predicting how changes in their structure affect their ability to deliver genes. This makes the process smarter and helps create more effective treatments.

GPU peak calling for epigenetics

LatchBio • 11 implied HN points • 21 Jan 25
đź•ą Technology Bioinformatics
  1. Peak calling is crucial for analyzing epigenetic data like ATAC-seq and ChIP-seq. It helps scientists identify important regions in the genome related to gene expression and diseases.
  2. The MACS3 algorithm is a common tool used for peak calling but struggles with handling large data volumes efficiently. Improving its implementation with GPUs can speed up analyses significantly.
  3. By using GPUs, researchers have achieved about 15 times faster processing speeds for peak calling, which is vital as more genetic data is generated in the field.