📣 We’re excited to announce the Graph Positional and Structural Encoder (GPSE) 🌐: The first graph encoder that learns highly transferable, unified representations for multiple positional encodings!
📜 Paper: https://t.co/8roPJA2Mvt
🛠 Code: https://t.co/eTzPNXvWu1
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Thrilled to launch the AI4BIO Center @CarnegieMellon! Our goal is to tackle grand challenges in understanding how cells work using AI/ML. Excited to help recruit faculty and foster collaboration across @SCSatCMU and campus. There is truly no place like CMU https://t.co/zSPoEhksee
Just published: "Current and future directions in network biology", a comprehensive review by leading experts in the field! Read it here: https://t.co/Ur9kUhy4OE #NetworkBiology#ISCB
The sequencing of the human genome changed little which genes are the focus of research attention.
The 8 most studied genes are:
TP53
TNF
EGFR
IL6
VEGFA
АРОЕ
TGFB1
MTHFR
Python is Rusty 🤡.
Refactored code in Polars (https://t.co/i4Rgx8rbE4) is 48x faster than the previous code in Pandas in one of my projects dealing with 100 million rows.
20 mins ➡️ 25 secs.
Excited to share that our new paper, led by Tatsushi Yokoyama, is out in @naturemethods . We developed improved genetically encoded green cAMP (cAMPinG1) and red calcium (RCaMP3) indicators for dual-color monitoring of cAMP and calcium signaling in vivo.
https://t.co/JtU4mLgBOM
The fantastic Machine Learning in Compbio #MLCB2023 papers are up at https://t.co/dcY6w1HZHh. Thanks @lawrennd & PMLR! We have talk recordings too at https://t.co/1XqBDACOZk.
Exciting News! Our DANCE version 1, "DANCE: a deep learning library and benchmark platform for single-cell analysis" is now finally published in Genome Biology (@GenomeBiology ) 🎉 !!!
DANCE has impacted the field, and got 290+ GitHub stars 🌟 before its official publication!