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Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. But, what exactly are they and how do they work? How can we use PGMs to discover patterns that are…

Quantitative Methods · Quantitative Biology 2010-02-22 Edoardo M Airoldi

Systems biology and whole-cell modelling are demanding increasingly comprehensive mathematical models of cellular biochemistry. These models require the development of simplified models of specific processes which capture essential…

Quantitative Methods · Quantitative Biology 2020-08-03 Peter J. Gawthrop , Peter Cudmore , Edmund J. Crampin

Background: Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides…

Graphics · Computer Science 2014-07-14 Shawn M. Waldon , Peter M. Thompson , Patrick J. Hahn , Russell M. Taylor

Biochars have been attracting renewed attention as economical and environmentally friendly carbon sequestration materials with a diverse range of applications. However, experimental developments may be limited by the lack of molecular-level…

Materials Science · Physics 2024-06-11 Rosie Wood , Ondrej Masek , Valentina Erastova

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based…

The intrinsic complexity of human biology presents ongoing challenges to scientific understanding. Researchers collaborate across disciplines to expand our knowledge of the biological interactions that define human life. AI methodologies…

Generating molecular graphs with desired chemical properties driven by deep graph generative models provides a very promising way to accelerate drug discovery process. Such graph generative models usually consist of two steps: learning…

Machine Learning · Statistics 2020-06-19 Chengxi Zang , Fei Wang

The automatic analysis of chemical literature has immense potential to accelerate the discovery of new materials and drugs. Much of the critical information in patent documents and scientific articles is contained in figures, depicting the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Lucas Morin , Martin Danelljan , Maria Isabel Agea , Ahmed Nassar , Valery Weber , Ingmar Meijer , Peter Staar , Fisher Yu

Understanding and designing biomolecules, such as proteins and small molecules, is central to advancing drug discovery, synthetic biology and enzyme engineering. Recent breakthroughs in artificial intelligence have revolutionized…

Computation and Language · Computer Science 2025-07-28 Xiang Zhuang , Keyan Ding , Tianwen Lyu , Yinuo Jiang , Xiaotong Li , Zhuoyi Xiang , Zeyuan Wang , Ming Qin , Kehua Feng , Jike Wang , Qiang Zhang , Huajun Chen

Molecular optimization, which transforms a given input molecule X into another Y with desirable properties, is essential in molecular drug discovery. The traditional translating approaches, generating the molecular graphs from scratch by…

Machine Learning · Computer Science 2020-08-17 Chaojie Ji , Yijia Zheng , Ruxin Wang , Yunpeng Cai , Hongyan Wu

Generating precise 3D molecular geometries is crucial for drug discovery and material science. While prior efforts leverage 1D representations like SELFIES to ensure molecular validity, they fail to fully exploit the rich chemical knowledge…

Machine Learning · Computer Science 2025-12-15 Zhanpeng Chen , Weihao Gao , Shunyu Wang , Yanan Zhu , Hong Meng , Yuexian Zou

Every molecule ever synthesised can be drawn as a 2D skeletal diagram, yet in modern property prediction this universally available representation has received less focus in favour of molecular graphs, 3D conformers, or billion-parameter…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Aaditya Baranwal , Akshaj Gupta , Shruti Vyas , Yogesh S Rawat

How far can we go with textual representations for understanding pictures? In image understanding, it is essential to use concise but detailed image representations. Deep visual features extracted by vision models, such as Faster R-CNN, are…

Computer Vision and Pattern Recognition · Computer Science 2021-06-28 Yusuke Hirota , Noa Garcia , Mayu Otani , Chenhui Chu , Yuta Nakashima , Ittetsu Taniguchi , Takao Onoye

Geometric, topological and graph theory modeling and analysis of biomolecules are of essential importance in the conceptualization of molecular structure, function, dynamics, and transport. On the one hand, geometric modeling provides…

Biomolecules · Quantitative Biology 2016-12-07 Kelin Xia , Guo-Wei Wei

Designing new molecules with a set of predefined properties is a core problem in modern drug discovery and development. There is a growing need for de-novo design methods that would address this problem. We present MolecularRNN, the graph…

Machine Learning · Computer Science 2019-06-03 Mariya Popova , Mykhailo Shvets , Junier Oliva , Olexandr Isayev

Proteins are the fundamental macromolecules that play diverse and crucial roles in all living matter and have tremendous implications in healthcare, manufacturing, and biotechnology. Their functions are largely determined by the sequences…

Biomolecules · Quantitative Biology 2024-09-17 Boqiao Lai

One of the major challenges in biology concerns the integration of data across length and time scales into a consistent framework: how do macroscopic properties and functionalities arise from the molecular regulatory networks - and how can…

Computational Engineering, Finance, and Science · Computer Science 2015-10-20 Dagmar Iber , Zahra Karimaddini , Erkan Ünal

Graphic design is an effective language for visual communication. Using complex composition of visual elements (e.g., shape, color, font) guided by design principles and aesthetics, design helps produce more visually-appealing content. The…

Human-Computer Interaction · Computer Science 2023-09-06 Danqing Huang , Jiaqi Guo , Shizhao Sun , Hanling Tian , Jieru Lin , Zheng Hu , Chin-Yew Lin , Jian-Guang Lou , Dongmei Zhang

Understanding the behaviour of biological systems requires a complex setting of in vitro and in vivo experiments, which attracts high costs in terms of time and resources. The use of mathematical models allows researchers to perform…

Computational Engineering, Finance, and Science · Computer Science 2009-11-30 Thomas Anung Basuki , Antonio Cerone , Rafael V. Carvalho

Understanding molecular structure and related knowledge is crucial for scientific research. Recent studies integrate molecular graphs with their textual descriptions to enhance molecular representation learning. However, they focus on the…

Artificial Intelligence · Computer Science 2025-06-02 Yibo Li , Yuan Fang , Mengmei Zhang , Chuan Shi