NIG, Microbiology
Joined November 2015
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New preprint: A large language model (LLM) powered framework for fully automated extraction and harmonization of subject metadata from research papers.
Applied to human gut microbiome studies:
- 26,435 papers processed
- 400,000+ samples integrated
- Metadata now searchable
Automated Harmonization and Large-Scale Integration of Heterogeneous Biomedical Sample Metadata Using Large Language Models biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
Koichi Higashi retweeted
🧬 Our “Behind the Paper” is now online at Springer Nature Communities:
“Active chromatin is not simply open—it forms compact domains that cohesin keeps from mixing.”
📖 A short story behind our recent @NatureGenet paper.
communities.springernature.c…
nature.com/articles/s41588-0…
Active chromatin is not simply open: it forms compact domains that cohesin keeps from mixing communities.springernature.c…
Koichi Higashi retweeted
Is euchromatin really “open”? 🧬 Using super-resolution imaging🔬 our new study @NatureGenet reveals: Euchromatin forms condensed domains in live cells. Cohesin constrains them and prevents domain mixing for proper transcriptional insulation🚧 🔗nature.com/articles/s41588-0… (1/2)
Koichi Higashi retweeted
Is euchromatin really “open”? 🧬Our new study @bioRxiv suggests otherwise. Using super-resolution imaging🔬 @shiori_iida @MasaAShimazoe reveals: Euchromatin forms condensed domains in live cells. Cohesin constrains them and prevents domain mixing. 🔗biorxiv.org/cgi/content/shor… (1/3)
Koichi Higashi retweeted
Our new paper is out @ScienceAdvances👇
science.org/doi/10.1126/scia…
🧬Our Repli-Histo labeling marks nucleosomes in euchromatin and heterochromatin in live human cells. 🔍@katsu_s_minami et al.have developed a chromatin behavior atlas within the nucleus. 1/2
L-formにおけるFtsZとNucleoid occlusionに関するおもしろい実験、解析で少し参加させていただきました。
nature.com/articles/s42003-0…
羊土社から来月出る「デルジーン」、PubMed論文に登場する順にヒト遺伝子を紹介するおもしろいコンセプトの本（買います）
いい切り口だなと思ったので、アイディアをパクって、「デルジーナス PubMed論文に登場する順 細菌・古細菌の属 Top1000」を作った。
derugenus.vercel.app/
解析手順。
1. NCBI Taxonomyから原核生物Genusラベル取得
2. PubMed APIで論文ヒット数取得
3. EuropePMC APIで引用回数上位論文取得
4. LLMでGenusごとに要約生成
5. v0でフロントエンド生成、Vercelでデプロイ
解析手順のコード。
github.com/khigashi1987/Deru…
PythonはClaude生成, Next.jsはv0生成, 文章はgpt-4o-mini生成。
Automatically process PDFs, Excel & DB records into unified metadata for cross-study analysis.
Available at:
🔧 github.com/khigashi1987/EMBE…
📊 github.com/khigashi1987/EMBE…
🌐 embersdb.jp
