Multi-omics data analysis has the potential to discover hidden molecular interactions,
revealing potential regulatory and/or signal transduction pathways for cellular processes of …

High-throughput molecular profiling technologies have produced high-dimensional multi-
omics data, enabling systematic understanding of living systems at the genome scale …

To derive expressive representations from high-dimensional and sparse multi-omics
samples, there has been existing research attempting to incorporate Gene Regulatory …

Interacting systems are ubiquitous in nature and engineering, ranging from particle
dynamics in physics to functionally connected brain regions. Revealing interaction laws is of …

Learning good representations on multi-relational graphs is essential to knowledge base
completion (KBC). In this paper, we propose a new self-supervised training objective for …

Multi-omics integration has demonstrated promising performance in complex disease
prediction. However, existing research typically focuses on maximizing prediction accuracy …

The molecular mechanisms and functions in complex biological systems currently remain
elusive. Recent high-throughput techniques, such as next-generation sequencing, have …

In recent years, enormous progress has been made in the field of Artificial Intelligence (AI).
Especially the introduction of Deep Learning and end-to-end learning, the availability of …

Given that heterogeneous information networks (HIN) encompass nodes and edges
belonging to different semantic types, they can model complex data in real-world scenarios …

A variety of real-world applications require the modeling and the simulation of dynamical
systems, eg, physics, transportation and climate. With the increase of complexity, it becomes …