$1.4 Billion! Merck of Germany Cooperates With AI Biotech Company; Musk Neuralink's First Brain-computer Interface Implant Plays Games With His Mind; Huang Renxun Gives a Lecture at Oregon State University
New achievements, new developments, and new perspectives of AI for Science——
* Fujitsu, Japan's leading IT company: Generative AI accelerates drug development
* Musk: Neuralink's first brain-computer interface implant recipient plays games with "thoughts"
* Merck and AI biotech company Caris reach cooperation
* AI protein design service provider "Tianwu Technology" completed tens of millions of yuan in Pre-A round of financing
* AbbVie acquires AI pharmaceutical company Landos Biopharma for $200 million
* Huang Renxun attended the Global Futures Forum held at Oregon State University
* The 2024 Academic Conference on Bioinformatics and Intelligent Information Processing will be held soon
See below for details~
Company NewsFujitsu, Japan's leading IT company: Generative AI accelerates drug development
Recently, Fujitsu and the government-backed RIKEN have collaborated to develop generative AI technology, using protein images taken with advanced cryogenic electron microscopes to apply generative AI to reproduce proteins as three-dimensional structures in motion. This technology predicts the state of target proteins 10 times faster than before. It is reported that Fujitsu is Japan's No. 1 IT manufacturer. It entered China in the 1970s and has invested more than 8 billion yuan in China. Its products are widely used in the automotive, food, medical, financial and other industries.
Musk Neuralink's first brain-computer interface implant uses "thoughts" to play games
Recently, Musk's company Neuralink live broadcast showed that Noland Arbaugh, the first person to receive a brain-computer interface, can now operate a computer through brain electrical signals. It is reported that the 29-year-old Noland Arbaugh is a retired chess player. A diving accident 8 years ago left him completely paralyzed. But after the brain chip was implanted, he was able to control the computer to play chess and even Mario Kart games through "thoughts". His performance contributed 271 pages of valuable data to Neuralink.
Merck and AI biotech company Caris reach cooperation
Recently, Merck KGaA of Germany announced a total of $1.4 billion in cooperation with Caris Life Sciences, an American AI biotechnology company. Caris will receive tiered royalties after the launch of its candidate drugs, and Merck will obtain exclusive global licenses for the development, manufacture and commercialization of ADC therapies for selected targets. Founded in 1668, Merck is a technology company focusing on three major areas: life sciences, pharmaceutical health and electronic technology. It has recently successfully expanded its oncology drug pipeline through ADC drugs. Founded in 1996, Caris is committed to using precision medicine to provide patients with more accurate and personalized treatment options.
AI protein design service provider "Tianwu Technology" completed tens of millions of yuan in Pre-A round of financing
Recently, Shanghai Tianwu Technology Co., Ltd. announced the successful completion of a Pre-A round of financing of tens of millions of yuan. This round of financing was led by Jinshajiang United Capital, and was followed by Bencao Capital, Xiaochi Capital and Sichuan Jiaoyan Capital. The funds raised will be mainly used to accelerate the industry application of universal large models of protein engineering and help upgrade the industry. "Tianwu Technology" was established in 2021. The core team mainly comes from Shanghai Jiaotong University. It is one of the earliest companies in China to deploy AI protein large models. The AI protein design large model AccelProtein developed by it adopts the Transformer architecture and masked language model, grasps the complex semantic connection between protein sequence and its function, and realizes end-to-end prediction from "sequence to function".
AbbVie acquires AI pharmaceutical company Landos Biopharma for $200 million
Recently, AbbVie announced that it has signed a definitive agreement with AI pharmaceutical company Landos Biopharma to acquire Landos for $212.5 million. The transaction is expected to be completed in the second quarter of 2024. Landos Biopharma was founded in 2017 and is an AI-based drug discovery company that focuses on immunity and metabolism and identifies important new molecular targets. According to the agreement, AbbVie will acquire Landos Biopharma's main pipeline NX-13 based on the AI drug development platform. NX-13 is a potential FIC oral NLRX1 agonist for the treatment of ulcerative colitis and has entered the clinical phase II stage.
Tools and Resources
Derm Foundation: Developing custom machine learning models for dermatology
Derm Foundation is a tool that generates embeddings from skin images. It can be used to develop custom machine learning models for dermatology with less data and computation than traditional model development methods.
Resource address:
https://github.com/Google-Health/imaging-research/tree/master/derm-foundation
Pymatgen: A Python library for materials analysis
Pymatgen (Python Materials Genomics) is an open source Python library for materials analysis. It has powerful materials analysis codes, defines categories for structures and molecules, and supports multiple electronic structure codes to power materials projects.
Resource address:
https://github.com/materialsproject/pymatgen
PubChemPy: A Chemistry Toolkit
PubChemPy relies on the PubChem database and is a chemical toolkit that provides a way to interact with PubChem in Python through the PUG REST web service, allowing users to perform functions such as file format conversion and chemical property retrieval by name, substructure, and similarity.
Resource address:
https://github.com/mcs07/PubChemPy
Ersilia: Centre for Modelling of Infectious and Neglected Diseases
Ersilia Model Hub is a unified platform for pre-trained AI/ML models dedicated to the research of infectious diseases and neglected diseases. The platform provides open source, low-code solutions to facilitate drug discovery.
Resource address:
https://github.com/ersilia-os/ersilia
Farmassist: Smart Agriculture Application Software
Farmassist is a smart agriculture application software for IoT and AI plant disease detection. It is built with Flutter and uses Firebase as the backend.
Resource address:
https://github.com/farmassistX/farmassist
EFAS: European Flood Awareness System
EFAS is the first operational system for monitoring and forecasting floods at European scale. Its goal is to support pre-flood preparedness measures in large transnational river basins and across Europe, and to inform the Emergency Response Coordination Centre (ERCC) of flood events that are occurring or are likely to occur at European scale.
Resource address:
https://european-flood.emergency.copernicus.eu/en/european-flood-awareness-system-efas
Research results
PLMSearch: Protein language model supports accurate and fast remote homolog sequence search
PLMSearch: Protein language model powers accurate and fast sequence search for remote homolog
*Source: Nature
* Field: Biomedicine
*Author: Fudan University Research Team
Original address:
https://www.nature.com/articles/s41467-024-46808-5
Deep learning-assisted automated multidimensional single-particle tracking in living cells
Deep Learning-Assisted Automated Multidimensional Single Particle Tracking in Living Cells
*Source: ACS Publications
* Field: Biomedicine
*Author: Xiamen University Research Team
Original address:
https://pubs.acs.org/doi/10.1021/acs.nanolett.3c04870
Historical Text Analysis of Contextualized Conceptual Representation (CCR) in Classical Chinese
Surveying the Dead Minds: Historical-Psychological Text Analysis with Contextualized Construct Representation (CCR) for Classical Chinese
*Source: arXiv
*Field: Medical Health
*Author: Peking University Research Team
Original address:
https://arxiv.org/abs/2403.00509
A general deep learning architecture for emissivity engineering
General deep learning framework for emissivity engineering
*Source: Nature
*Field: Materials Chemistry
*Author: Research team from Huazhong University of Science and Technology
Original address:
https://www.nature.com/articles/s41377-023-01341-w
Using machine learning to predict the impact of future drought on millet yield in northern Shanxi
Projection of future drought impacts on millet yield in northern Shanxi of China using ensemble machine learning approach
*Source: ELSEVIER
* Field: Agriculture, forestry and animal husbandry
*Author: Research team from China Agriculture and Forestry University
Original address:https://www.sciencedirect.com/science/article/abs/pii/S0168169924001169
Upcoming Events
Bioinformatics and Intelligent Information Processing 2024 Academic Conference
The 2024 Academic Conference on Bioinformatics and Intelligent Information Processing, hosted by the China Artificial Intelligence Society and others, will be held at the Grand Palace Hotel in Guilin, Guangxi from June 14th to 16th.
The theme of this conference is "Digital Biology in the Era of AI Big Models". Many well-known experts and scholars in the fields of artificial intelligence, life sciences, medical sciences, etc. are invited to give special reports. The themes of the sub-venues include biological analysis and intelligent processing algorithms, biological multi-omics data analysis, intelligent drug design, precision medicine and big data, language big models and biological big models, etc.
Event Link:
http://www.biip2024gl.com/
Global Futures Forum : Artificial Intelligence
The "Global Futures Forum: Artificial Intelligence" was held at Oregon State University on April 12. The conference invited NVIDIA founder Huang Renxun, Oregon State University Assistant Professor of Forestry, Ecosystems and Society Loren Albert, and University of Washington Experimental Art and Digital Media Ph.D. Chari Glogovac-Smith. Topics shared at the conference included climate science and AI, and the impact of AI on the workforce and the economy.
Event Link:
Event Review
Chalmers AI4Science Workshop
Recently, the Chalmers AI4Science workshop organized by Simon Olsson and Rocío Mercado was held on the theme of "Kernel Methods for Koopman-based Modeling in Molecular Simulation". The event was presented by Dr. Feliks Nüske, research group leader at the Max-Planck Institute for Dynamics of Complex Technical Systems, who introduced the latest results on the effective use of kernel-based dynamic mode decomposition (EDMD) in the context of molecular simulations, and showed how to use low-rank approximations based on random Fourier features (RFF) to effectively solve the resulting linear algebra problems.
Event Link:
https://psolsson.github.io/AI4ScienceSeminar
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