The integration of the latest breakthroughs in biochemistry and biotechnology from one side and high-performance computing and computational modeling from the other enables remarkable advances in the fields of health care, drug discovery, genome research, systems biology, and so on. By integrating all these developments together, scientists are creating new exciting personal therapeutic strategies to live longer and have healthier lifestyles that were unfeasible not long ago. These efforts have created new fields of research such as bioinformatics, computational biology, or computational chemistry that work into many different areas of research, such as life sciences, where there are many examples of scientific applications for discovering biological and medical unknown factors that could greatly benefit from increased computational resources. However, we are witnessing a steady transition to heterogeneous architectures, where traditional CPUs and accelerators like graphics processing units (GPUs), Intel MIC/Xeon Phi, and field programmable gate arrays are combined together to maintain the traditional increment in performance over the years. The underlying computational model of such architectures relies on massive vectorization to reduce the energy per instruction. Traditional algorithms are often tailored to sequential or modestly parallel-based architectures that may not fit within this landscape of computation. However, novel algorithms that are inspired by nature procedures, such as bioinspired metaheuristics (genetic algorithms, ant colony optimization, swarm optimization, etc.), artificial neural networks, just to mention a few, are gaining special interest in the community as they are massively parallel by its definition. This special issue gathers selected papers of the workshop on Bioinformatics and High Performance Computing (BIO-HPC) that was held at Eugene, Oregon, USA, on August 13–16, 2018. The purpose of the workshop is to look for original research works that explore the intersection between both the algorithm design and the hardware platforms to deal with the emergent challenges of the next century in the field of bioinformatics, computational biology, and computational chemistry. In this regard, one of the main objectives of this special issue was gathering articles about the main trends in parallel processing, algorithm definition, and problem-domain requirements altogether, which may anticipate future solutions to be translated into real benefits to the society. The following papers present research on the development of novel and high-performance methods for different relevant bioinformatics problems, such as drug discovery, molecular dynamics, DNA hydroxymethylation analysis, epistatic interactions, and human respiratory simulations in the context of HPC. I can definitely say that some of these papers can really make an impact in their respective areas of application. The workshop was made possible, thanks to sponsorship from the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia under Project 20813/PI/18 and by Spanish Ministry of Science, Innovation and Universities under grants TIN2016-78799-P (AEI/ FEDER, UE) and RTC-2017-6389-5. I would like to express our warm thanks to them.

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客座编者注：关于生物信息学中新型高性能计算算法和平台的特刊

一方面将生物化学和生物技术的最新突破与另一方面的高性能计算和计算建模相结合，可以在医疗保健、药物发现、基因组研究、系统生物学等领域取得显着进展。通过将所有这些发展整合在一起，科学家们正在创造新的令人兴奋的个人治疗策略，以延长寿命并拥有不久前无法实现的更健康的生活方式。这些努力创造了新的研究领域，如生物信息学、计算生物学或计算化学，这些领域适用于许多不同的研究领域，如生命科学，其中有许多科学应用的例子来发现生物和医学未知因素，这些因素可以极大地发挥作用。受益于增加的计算资源。然而，我们正在目睹向异构架构的稳定过渡，在这种架构中，传统 CPU 和加速器（如图形处理单元 (GPU)、英特尔 MIC/Xeon Phi 和现场可编程门阵列）结合在一起，以保持多年来的传统性能增量。这种架构的底层计算模型依赖于大规模矢量化来减少每条指令的能量。传统算法通常是为顺序或适度并行的架构量身定制的，这些架构可能不适合这种计算环境。然而，受自然程序启发的新算法，例如仿生元启发式算法（遗传算法、蚁群优化、群优化等）、人工神经网络，仅举几例，正在社区中获得特别的兴趣，因为它们的定义非常相似。本期特刊收集了 2018 年 8 月 13 日至 16 日在美国俄勒冈州尤金市举行的生物信息学和高性能计算 (BIO-HPC) 研讨会的精选论文。 该研讨会的目的是寻找原创研究作品探索算法设计和硬件平台之间的交叉点，以应对下个世纪生物信息学、计算生物学和计算化学领域的新挑战。在这方面，本期特刊的主要目标之一是收集有关并行处理、算法定义和问题域要求的主要趋势的文章，预计未来的解决方案将转化为对社会的真正利益。以下论文介绍了针对不同相关生物信息学问题的新型高性能方法的开发，例如药物发现、分子动力学、DNA 羟甲基化分析、上位相互作用和 HPC 背景下的人类呼吸模拟。我可以肯定地说，其中一些论文确实可以在各自的应用领域产生影响。研讨会得以举办，这要归功于塞内卡德尔中心协调基金会在项目 20813/PI/18 下的穆尔西亚地区调查和西班牙科学、创新和大学部在 TIN2016-78799-P（ AEI/FEDER, UE) 和 RTC-2017-6389-5。