Peachie

[Tominaga K. (tomiken) @pacyc1841]

GitHub - faridrashidi/cnsplots: 🎨 Toolkit for generating publication-quality plots for Cell, Nature and Science journals · GitHub https://t.co/F0NoGjFYCw

[Ming "Tommy" Tang @tangming2005]

A nice python package for creating Publication-Ready Scientific Plots https://t.co/WX2kvXtzxU

if you use R, take a look at https://t.co/HgyiQA7CbA

[BioTender @Junioryu136689]

A new molecular biology workflow for Claude Science.

Introducing Motif — a molecular biology workbench that brings plasmid design, cloning workflows, sequence analysis, and biological engineering tasks into your Claude workflow.

From sequence to solution

A glimpse of how AI assistants are moving beyond text generation and becoming true scientific collaborators.

Open source: https://t.co/Tnj0RGd1c8

#AI4Science #BioAI #ClaudeScience #SyntheticBiology #MolecularBiology

[Codez @0xCodez]

Andrew Ng just released a 1-hour course on building agentic knowledge Graphs from scratch:

• 00:00 - Introduction to agentic knowledge Graphs
• 03:07 - Construction of agentic Graphs
• 14:00 - Architecture of multi-agent systems
• 23:00 - Building agentic graphs with Google ADK
• 01:06:03 - Why Graphsare the future of agentic AI

Worth more than 10 articles on loop engineering.

Watch it today, then read how to become a graph engineer in the article below.

[🌻 Katie 🌻 @finallyimfound7]

Hesitate in 2026? Oh how I love a healed Joe 🥺

[Ming "Tommy" Tang @tangming2005]

10 courses to get you started with bioinformatics 🧵 Bookmark!

[Ming "Tommy" Tang @tangming2005]

Want to master bioinformatics data visualization?
I almost quit when I first tried ggplot2.

But once I “got it,” it changed how I saw data forever.
Here’s the hard-won path that makes ggplot2 click. 🧵

[Ming "Tommy" Tang @tangming2005]

1/ Ever see a stunning bioinformatics figure and think:
“How on earth did they make that?”
Let’s break it down so you can recreate it.

[Zikun-Yang 杨子坤 🐵 @zikun__yang]

Now you can use VAMPIRE to classify #TandemRepeat across populations and explore repeat-type-aware copy number variation.

See here for detailed turtorials:
https://t.co/QTJvWaWVRa

[Ming "Tommy" Tang @tangming2005]

2. learning-bioinformatics-at-home
https://t.co/PvNJjtMtD7
I started this repo 6 years ago at Harvard FAS informatics.

[Ming "Tommy" Tang @tangming2005]

Two resources to learn bioinformatics yourself:
1. Path to a free self-taught education in Bioinformatics!
https://t.co/ahSwaYNCbU

[Ming "Tommy" Tang @tangming2005]

1/ Bioinformatics takes years to master.
Not because it’s hard.
But because so much of what matters… no one writes down.
Let me explain

[Ming "Tommy" Tang @tangming2005]

1/ Exploratory Data Analysis (EDA) is the first step in any data analysis journey.

When working with RNA-seq data, one of the most commonly used techniques is Principal Component Analysis (PCA).

But what exactly is PCA, and why does it matter? Let’s break it down. 🧵👇

[Ming "Tommy" Tang @tangming2005]

Depending on your data type, use the right plot to tell the story.
A nice interactive app to determine what plots you need
https://t.co/scV7uNKovr

[Codez @0xCodez]

https://t.co/eJB3TgyJwV

[Codez @0xCodez]

A senior Anthropic engineer just dropped 11-page PDF on "Loop Engineering" for agentic systems.

The shift: you stop prompting the agent. You build the system that prompts it instead.

Schedule → Discover → Build → Verify → Repeat

Every loop runs one turn, five moves:

• Discovery: it finds its own work - failing CI, open issues, recent commits - instead of being handed a list.

• Handoff: each task gets an isolated git worktree so parallel agents don't collide.

• Verification: a second agent, told to assume the code is broken, reviews the first. The "thing that can say no."

• Persistence: results get written to disk, never left in a context window that gets flushed.

• Scheduling: an automation wakes it on a timer. That's what makes it a loop.

The key insight: an agent grading its own work always praises it.

This 11-page PDF changed how I'm building agentic systems today.

Read it now, then explore the article below.

[Rahul @sairahul1]

🚨 Karpathy was right.

He warned that 90% of AI advice dies in 6 months

spoiler: most tools will not even survive 90 days

this guy is literally giving away the exact 2026 playbook for AI Agents.

he covers what to learn, how to build, and when to skip 👀

↓ read this today

[Oliver Prompts @oliviscusAI]

Turn Claude Code into a full academic research team with this guide.

> Deep Research: 13 agents, 8 modes
> Academic Paper: 12 agents, 11 modes
> Academic Paper Reviewer: 7 agents
> Academic Pipeline: 10-stage orchestrator with citation verification

Free for non-commercial use.

[Khairallah AL-Awady @eng_khairallah1]

this is f*cking gold

How to build your first AI agent (Full guide)

if I had this a year ago, I would've shipped my first agent in a day instead of 2 weeks

in the right hands, this changes everything: