AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Explore and Practice of China's Intelligent “New Engineering” — Based on the Grounded Theory

In the era of the Industrial Revolution 4.0, emerging intelligent information technologies represented by the Internet of Things, big data, artificial intelligence, etc. are triggering a new round of educational reforms, driving human education to transition to intelligent education. This article adopts the 612 national-level new engineering research and practice projects released by China in 2018 that involve the integration of new engineering and wisdom education in universities and colleges that also implement the integration of the two in addition to the New Engineering Research and Practice Project，A total of 80 colleges and universities practice samples as research objects，With the help of the grounded theory system, a fusion model consisting of 755 original sentences, 77 concepts, 25categories, 7main categories, and 3 core categories-the TCG model. Its integration path is: Block chain: more open and more credible new ideas; Internet + education: the construction of a curriculum system that combines theory and practice with individuality and multiple coexistence; emotional skills perception + cloud computing: intelligent new teachers Strength training; AI + VR: construction of an open and immersive second learning world; big data + the Internet of Things: the establishment of a precise and intelligent management system; big data + artificial intelligence: the construction of a new mechanism of evaluation and incentives; the Internet of Things + none Seamless Interconnection: Comprehensive Perception of Government-Industry-Research Cooperation System.</jats:p

A study on relation extraction of historical figures based on bibliographic description

Figure relation extraction is an important and hard field in information extraction. In this paper, aiming to improve the performance for relation extraction of historical figures, we propose a novel method based on bibliographic description. In the proposed method, by analyzing the species and co-occurrence relation of responsibility in a bibliographic record, we combine diverse person responsibility, person name and time as features, whose values are the quantity of the species clustering concerned, to build a Decision Tree model. Accordingly, relation extraction of historical figures is performed through the model. It is experimentally shown that on average, 83.3% and 83.0% in precision and recall rate are achieved respectively without more linguistic knowledge and complex classifiers. ? 2011 IEEE.EI