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  • Multi-omics studies have been increasingly used to better understand biological samples and infer molecular interactions. Nevertheless, a number of challenges must still be addressed to take full advantage of multi-omics data and to avoid reaching potentially incorrect conclusions.

    • Sonia Tarazona
    • Angeles Arzalluz-Luque
    • Ana Conesa
  • Development in digital-twin technology has been rapidly growing across a range of industries and disciplines. However, to ensure a wider and more robust adoption of such technology, various challenges must be addressed by the computational science community.

    • Steven A. Niederer
    • Michael S. Sacks
    • Karen Willcox
  • The field of biomolecular modeling has thrived by exploiting state-of-the-art technological advances. In this Perspective, the role of software and hardware advances, and the disparity and synergy between knowledge-based and physics-based methods are discussed and explored.

    • Tamar Schlick
    • Stephanie Portillo-Ledesma
  • Quantum computing has the potential to assist with myriad tasks in science. In this Perspective, the applicability and promising directions of quantum computing in computational biology, genetics and bioinformatics is evaluated and discussed.

    • A. K. Fedorov
    • M. S. Gelfand
  • There have been substantial developments in weather and climate prediction over the past few decades, attributable to advances in computational science. The rise of new technologies poses challenges to these developments, but also brings opportunities for new progress in the field.

    • Peter Bauer
    • Peter D. Dueben
    • Nils P. Wedi
  • While estimating causality from observational data is challenging, quasi-experiments provide causal inference methods with plausible assumptions that can be practical to a range of real-world problems.

    • Tony Liu
    • Lyle Ungar
    • Konrad Kording