AF: 4th Workshop on Biological Distributed Algorithms (BDA 2016)

AF：第四届生物分布式算法研讨会（BDA 2016）

• 批准号: 1624201
• 负责人: Saket Navlakha
• 金额: $ 1万
• 依托单位: The Salk Institute for Biological Studies
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1624201&HistoricalAwards=false
• 关键词: AF; 4th; Workshop; Biological; Distributed

The goal of the Biological Distributed Algorithms (BDA) workshop is to bring together computer scientists and biologists interested in studying the relationships between distributed algorithms and distributed biological systems, including ant colonies, slime molds, the immune system, and the brain. The workshop will include invited talks together with oral and poster presentations selected by the workshop's program committee. This is the 4th BDA meeting. This year, the workshop will be co-located with a premiere distributed computing conference, PODC. In 2015, BDA was held as a stand-alone 2-day workshop at MIT in Boston, MA. In 2013 and 2014, BDA was co-located with another premiere distributed computing conference, DISC, in Austin, TX and Jerusalem, Israel, respectively. Each year, we have seen growing attendance and submissions. The funds sought will be used to provide travel support for 10-15 students and post-docs, including women and minorities, to attend and present their work (oral or poster) at the workshop. Since young researchers, especially students and postdocs, tend to be the driving force behind successful interdisciplinary collaborations, we will dedicate most of the slots in the upcoming BDA meeting to works presented by students and postdocs. Our experience in the past BDA meetings shows that students and postdocs often have difficulty securing travel funds for such events, therefore we will encourage their participation by offering them generous travel grants. We hope to introduce young researchers to this exciting and emerging area of cross-disciplinary research, and help them establish collaborations for the future. Distributed systems are prevalent in computer science and biology. Both domains rely on networks of interacting entities - molecules, cells, and organisms in biology; sensor, mobile, and autonomous robot devices in computer science - to coordinate output responses to inputs, route resources, and navigate through environments. Both types of systems also seek solutions to these problems that are inherently efficient, robust, and adaptive with respect to changes expected in natural and competitive environments. These connections suggest that by thinking computationally about the settings, requirements, and goals of information processing within distributed biological systems, we can achieve two complementary goals: First, we can use insights about how biological systems solve computational problems to aid in designing more flexible, robust, and adaptive distributed algorithms. Second, we can use, develop, or adapt existing distributed computing theory to help understand the behavior of biological systems and propose new, testable hypotheses to determine how well such models fit the observed behavior of the biological system. By bringing together both biologists and computer scientists, we aim to cross-fertilize the important and timely ideas that both domains can offer to one another.

生物分布式算法(BDA)研讨会的目标是将对研究分布式算法和分布式生物系统(包括蚁群、黏菌、免疫系统和大脑)之间的关系感兴趣的计算机科学家和生物学家聚集在一起。研讨会将包括受邀演讲以及由研讨会项目委员会挑选的口头和海报演示文稿。这是BDA的第四次会议。今年，研讨会将与首屈一指的分布式计算会议PODC共址。2015年，BDA在马萨诸塞州波士顿的麻省理工学院作为一个为期两天的独立研讨会举行。2013年和2014年，BDA分别在德克萨斯州奥斯汀和以色列耶路撒冷与另一个首屈一指的分布式计算会议DISC共同举办。每年，我们都看到越来越多的参观者和提交的作品。所筹资金将用于为10-15名学生和博士后，包括妇女和少数群体，提供旅行支助，以参加讲习班并在讲习班上介绍他们的作品(口头或海报)。由于年轻的研究人员，特别是学生和博士后，往往是成功的跨学科合作的驱动力，我们将把即将到来的BDA会议的大部分时间用来介绍学生和博士后的作品。我们在过去的BDA会议上的经验表明，学生和博士后往往很难获得此类活动的旅费，因此我们将通过向他们提供慷慨的旅费补助来鼓励他们参与。我们希望向年轻的研究人员介绍这一令人兴奋的新兴跨学科研究领域，并帮助他们建立未来的合作关系。分布式系统在计算机科学和生物学中非常普遍。这两个领域都依赖于相互作用的实体网络--生物学中的分子、细胞和有机体；计算机科学中的传感器、移动和自主机器人设备--以协调对输入的输出响应、路由资源和在环境中导航。这两种类型的系统还寻求针对这些问题的解决方案，这些解决方案对于自然和竞争环境中预期的变化具有内在的高效、健壮和适应性。这些联系表明，通过计算思考分布式生物系统中信息处理的设置、要求和目标，我们可以实现两个互补的目标：第一，我们可以使用对生物系统如何解决计算问题的见解来帮助设计更灵活、更健壮和更适应的分布式算法。其次，我们可以使用、开发或调整现有的分布式计算理论来帮助理解生物系统的行为，并提出新的、可测试的假设来确定这些模型与生物系统观察到的行为的匹配程度。通过将生物学家和计算机科学家聚集在一起，我们的目标是交叉培养这两个领域可以相互提供的重要和及时的想法。