@article{SalihogluSrivastavaLiangetal.2023,
  author    = {Salihoglu, Rana and Srivastava, Mugdha and Liang, Chunguang and Schilling, Klaus and Szalay, Aladar and Bencurova, Elena and Dandekar, Thomas},
  title     = {PRO-Simat: Protein network simulation and design tool},
  series = {Computational and Structural Biotechnology Journal},
  volume    = {21},
  journal   = {Computational and Structural Biotechnology Journal},
  issn      = {2001-0370},
  doi       = {10.1016/j.csbj.2023.04.023},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-350034},
  pages     = {2767-2779},
  year      = {2023},
  abstract  = {PRO-Simat is a simulation tool for analysing protein interaction networks, their dynamic change and pathway engineering. It provides GO enrichment, KEGG pathway analyses, and network visualisation from an integrated database of more than 8 million protein-protein interactions across 32 model organisms and the human proteome. We integrated dynamical network simulation using the Jimena framework, which quickly and efficiently simulates Boolean genetic regulatory networks. It enables simulation outputs with in-depth analysis of the type, strength, duration and pathway of the protein interactions on the website. Furthermore, the user can efficiently edit and analyse the effect of network modifications and engineering experiments. In case studies, applications of PRO-Simat are demonstrated: (i) understanding mutually exclusive differentiation pathways in Bacillus subtilis, (ii) making Vaccinia virus oncolytic by switching on its viral replication mainly in cancer cells and triggering cancer cell apoptosis and (iii) optogenetic control of nucleotide processing protein networks to operate DNA storage. Multilevel communication between components is critical for efficient network switching, as demonstrated by a general census on prokaryotic and eukaryotic networks and comparing design with synthetic networks using PRO-Simat. The tool is available at https://prosimat.heinzelab.de/ as a web-based query server.},
  language  = {en}
}
@article{WangLiuXiaoetal.2023,
  author    = {Wang, Xiaoliang and Liu, Xuan and Xiao, Yun and Mao, Yue and Wang, Nan and Wang, Wei and Wu, Shufan and Song, Xiaoyong and Wang, Dengfeng and Zhong, Xingwang and Zhu, Zhu and Schilling, Klaus and Damaren, Christopher},
  title     = {On-orbit verification of RL-based APC calibrations for micrometre level microwave ranging system},
  series = {Mathematics},
  volume    = {11},
  journal   = {Mathematics},
  number    = {4},
  issn      = {2227-7390},
  doi       = {10.3390/math11040942},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-303970},
  year      = {2023},
  abstract  = {Micrometre level ranging accuracy between satellites on-orbit relies on the high-precision calibration of the antenna phase center (APC), which is accomplished through properly designed calibration maneuvers batch estimation algorithms currently. However, the unmodeled perturbations of the space dynamic and sensor-induced uncertainty complicated the situation in reality; ranging accuracy especially deteriorated outside the antenna main-lobe when maneuvers performed. This paper proposes an on-orbit APC calibration method that uses a reinforcement learning (RL) process, aiming to provide the high accuracy ranging datum for onboard instruments with micrometre level. The RL process used here is an improved Temporal Difference advantage actor critic algorithm (TDAAC), which mainly focuses on two neural networks (NN) for critic and actor function. The output of the TDAAC algorithm will autonomously balance the APC calibration maneuvers amplitude and APC-observed sensitivity with an object of maximal APC estimation accuracy. The RL-based APC calibration method proposed here is fully tested in software and on-ground experiments, with an APC calibration accuracy of less than 2 mrad, and the on-orbit maneuver data from 11-12 April 2022, which achieved 1-1.5 mrad calibration accuracy after RL training. The proposed RL-based APC algorithm may extend to prove mass calibration scenes with actions feedback to attitude determination and control system (ADCS), showing flexibility of spacecraft payload applications in the future.},
  language  = {en}
}