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Earlier sources: Science
Science investigates the natural world through observation, experiments, and mathematical models. Explore papers and developments in biology, medicine, materials, neuroscience, physics, climate, and mathematics; a reported finding is not necessarily established consensus.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗1333 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- Hacker News · Posted on Hacker News · First archived
Show HN: Health Explorer – See how genes shape health, from DNA to treatment ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
How Protein Took over the World ↗
https://archive.is/CbkfI
- Hacker News · Posted on Hacker News · First archived
PVX-001: open-source Covid-19 vaccine starts Phase 1 trial ↗
Hacker News discussion.
- arXiv · Published · First archived
Clarifying tipping terminology ↗
The notion of tipping points and related terminology have so far had inconsistent and sometimes confusing definitions in both scientific and popular literature. While it is difficult for the scientific community to align popular usage of the term tipping point with a precise definition, technical usage of related terms would benefit from greater consistency and rigor. Toward this end, we offer a systematic set of terms to clarify formal communication around potential tipping dynamics, with focus on examples from Earth system dynamics.
- Hacker News · Posted on Hacker News · First archived
3D structure of DNA may explain how cephalopods evolved complex brains ↗
Hacker News discussion.
- arXiv · Published · First archived
Learning native eddy-resolving ocean dynamics outperforms coarse emulation and downscaling ↗
Eddy-resolving ocean simulations are essential for representing mesoscale dynamics that regulate ocean circulation, energy transport, and climate variability. However, they are costly to generate, store, and share. Artificial intelligence (AI) may help, but it remains unclear whether high-resolution ocean fields can be faithfully represented by evolving ocean states at coarse resolution followed by spatial downscaling, or whether dynamical evolution needs to be learned directly from native high-resolution simulations. We show that directly learning dynamical evolution on a 0.1$^\circ$ grid pro…
- GitHub · Repository created · First archived
Dicklesworthstone/jeffs_math_explainer_videos ↗
Narrated, 3Blue1Brown-style 4K math explainer videos built in Rust with franken_manim (native TeX, no LaTeX, no Python) and voiced by FrankenTTS. Every number computed and oracle-checked, every line ASR-verified and never time-stretched, every frame looked at, with a warm procedural score under the voice.
- Hacker News · Posted on Hacker News · First archived
Show HN: tgv: Genome viewer for you and your agents ↗
Hi HN, I’m sharing tgv, a new kind of genome viewer built for humans-agent collaboration in genomics. I work in a cancer diagnostics lab and we check cancer patients’ sequencing data in genome viewers every day. Frustrated by the standard tools, last year I built tgv, a Vim-style, keyboard-driven genome viewer. In 2026, while agents are scarily good at bioinformatics, bioinformatics tools haven’t kept up. tgv now brings a new kind of research wor…
- OpenAlex · Published · First archived
FunFOLD5: Combining Localised Templates and Structural Homology for Accurate Predictions of Biologically Relevant Protein–Ligand Interactions ↗
Abstract Motivation A central challenge in protein–ligand modelling is to predict not only the presence of an interaction, but also the correct ligand identity, binding-site location, and biologically relevant bound conformation. While recent deep learning approaches such as AlphaFold3 and Boltz-2 have demonstrated impressive accuracy in modelling protein–ligand complexes, these methods typically require prior knowledge of the ligand, focus on a single dominant binding pose, and rely heavily on large training datasets. Template-based methods offer a complementary solution by leveraging experim…
- OpenAlex · Published · First archived
Prediction of Tumor Complete Response Using Genomic and Clinical Data in Solid Cancer Undergoing Definitive Radiation Therapy ↗
In this retrospective, single-center observational study, targeted next-generation sequencing (NGS) was performed on pre-radiation therapy (RT) tumor specimens to identify genomic features associated with RT response and clinical outcomes. This study included 77 eligible patients with esophageal squamous cell carcinoma (ESCC, n = 23), non-human papilloma virus-related head and neck squamous cell carcinoma (HNSCC, n = 24), and rectal adenocarcinoma (RAC, n = 30) treated between 2014 and 2020. Treatment was employed for definitive aim (chemoradiotherapy or pre-operative chemoradiotherapy followe…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Science
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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