显示样式:     当前期刊: Advances in Physics    加入关注    导出
我的关注
我的收藏
您暂时未登录!
登录
  • Inverse statistical problems: from the inverse Ising problem to data science
    Adv. Phys. (IF 21.818) Pub Date : 2017-06-29
    H. Chau Nguyen, Riccardo Zecchina, Johannes Berg

    Inverse problems in statistical physics are motivated by the challenges of ‘big data’ in different fields, in particular high-throughput experiments in biology. In inverse problems, the usual procedure of statistical physics needs to be reversed: Instead of calculating observables on the basis of model parameters, we seek to infer parameters of a model based on observations. In this review, we focus on the inverse Ising problem and closely related problems, namely how to infer the coupling strengths between spins given observed spin correlations, magnetizations, or other data. We review applications of the inverse Ising problem, including the reconstruction of neural connections, protein structure determination, and the inference of gene regulatory networks. For the inverse Ising problem in equilibrium, a number of controlled and uncontrolled approximate solutions have been developed in the statistical mechanics community. A particularly strong method, pseudolikelihood, stems from statistics. We also review the inverse Ising problem in the non-equilibrium case, where the model parameters must be reconstructed based on non-equilibrium statistics.

    更新日期:2017-08-18
Some contents have been Reproduced with permission of the American Chemical Society.
Some contents have been Reproduced by permission of The Royal Society of Chemistry.
化学 • 材料 期刊列表
Wiley论文编辑服务,每月大奖送不停!
深圳大学-同济大学联合招聘博士后(税后年薪30万)
华中师范大学第一届国际青年学者化学科学论坛
【问答】苯发生亲核取代反应可能的机理是什么?
X-MOL近期新增451种期刊(20171216)
2017年中科院JCR分区化学大类列表
试剂库存管理
化合物查询
down
wechat
bug