• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 1,294 matches

• 2021
• 
  Weichen Sun, Zhijing Zhang, Weimin Zhang:
  A Coaxial Alignment Method for Large Flange Parts Assembly Using Multiple Local Images. IEEE Access 9: 16716-16727 (2021)
• 
  Lamiche Chaabane:
  An enhanced cooperative method to solve multiple-sequence alignment problem. Int. J. Data Min. Model. Manag. 13(1/2): 1-16 (2021)
• 
  Dengpeng Xing, Fangfang Liu, De Xu:
  Joint Alignment and Simultaneous Insertion of Multiple Objects in Precision Assembly. IEEE Trans. Ind. Informatics 17(1): 230-239 (2021)
• 
  Weihua Liu, Zhe Zhang, Lixun Huang, Jin Xu, Xueyan Chen:
  Alignment Chain-Based Closed-Form IA Solution for Multiple User MIMO Interference Networks. IEEE Trans. Veh. Technol. 70(2): 1518-1527 (2021)
• 2020
• 
  Vipin Vijayan, Shawn Gu, Eric T. Krebs, Lei Meng, Tijana Milenkovic:
  Pairwise Versus Multiple Global Network Alignment. IEEE Access 8: 41961-41974 (2020)
• 
  Andrew F. Neuwald, Christopher J. Lanczycki, Theresa K. Hodges, Aron Marchler-Bauer:
  Obtaining extremely large and accurate protein multiple sequence alignments from curated hierarchical alignments. Database J. Biol. Databases Curation 2020 (2020)
• 
  Antonio Benítez-Hidalgo, Antonio J. Nebro, José Francisco Aldana Montes:
  Sequoya: multiobjective multiple sequence alignment in Python. Bioinform. 36(12): 3892-3893 (2020)
• 
  Timo Lassmann:
  Kalign 3: multiple sequence alignment of large datasets. Bioinform. 36(6): 1928-1929 (2020)
• 
  Etminan Naznooshsadat, Parvinnia Elham, Sharifi-Zarchi Ali:
  FAME: fast and memory efficient multiple sequences alignment tool through compatible chain of roots. Bioinform. 36(12): 3662-3668 (2020)
• 
  Mohammad Arifur Rahman, Huzefa Rangwala:
  IDMIL: an alignment-free Interpretable Deep Multiple Instance Learning (MIL) for predicting disease from whole-metagenomic data. Bioinform. 36(Supplement-1): i39-i47 (2020)
• 
  Fabian Sievers, Desmond G. Higgins:
  QuanTest2: benchmarking multiple sequence alignments using secondary structure prediction. Bioinform. 36(1): 90-95 (2020)
• 
  Chengxin Zhang, Wei Zheng, S. M. Mortuza, Yang Li, Yang Zhang:
  DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins. Bioinform. 36(7): 2105-2112 (2020)
• 
  Weiya Chen, Chun Yao, Yingzhong Guo, Yan Wang, Zhidong Xue:
  pmTM-align: scalable pairwise and multiple structure alignment with Apache Spark and OpenMP. BMC Bioinform. 21(1): 426 (2020)
• 
  Hiroyuki Fukuda, Kentaro Tomii:
  DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment. BMC Bioinform. 21(1): 10 (2020)
• 
  Anna Pia Lohfink, Florian Wetzels, Jonas Lukasczyk, Gunther H. Weber, Christoph Garth:
  Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees. Comput. Graph. Forum 39(3): 343-355 (2020)
• 
  Luay Alawneh, Mohammed A. Shehab, Mahmoud Al-Ayyoub, Yaser Jararweh, Ziad A. Al-Sharif:
  A scalable multiple pairwise protein sequence alignment acceleration using hybrid CPU-GPU approach. Clust. Comput. 23(4): 2677-2688 (2020)
• 
  Seyyed Hossein Hosseini-Fakhr, Abolfazl Falahati:
  Interference alignment in two-hop multiple-input multiple-output interference channel under various CSI and antenna correlation. IET Commun. 14(20): 3599-3606 (2020)
• 
  T. Gururaj, G. M. Siddesh:
  Optimised parallel implementation with dynamic programming technique for the multiple sequence alignment. Int. J. Big Data Intell. 7(3): 148-156 (2020)
• 
  Ali Dabba, Abdelkamel Tari, Djaafar Zouache:
  Multiobjective artificial fish swarm algorithm for multiple sequence alignment. INFOR Inf. Syst. Oper. Res. 58(1): 38-59 (2020)
• 
  Ayalew Kassahun, Bedir Tekinerdogan:
  BITA*: Business-IT alignment framework of multiple collaborating organisations. Inf. Softw. Technol. 127: 106345 (2020)
• 
  Sanjay S. Bankapur, Nagamma Patil:
  ProgSIO-MSA: Progressive-based single iterative optimization framework for multiple sequence alignment using an effective scoring system. J. Bioinform. Comput. Biol. 18(2): 2050005:1-2050005:28 (2020)
• 
  Justin Chu, Hamid Mohamadi, Emre Erhan, Jeffery Tse, Readman Chiu, Sarah Yeo, Inanç Birol:
  Mismatch-tolerant, alignment-free sequence classification using multiple spaced seeds and multiindex Bloom filters. Proc. Natl. Acad. Sci. USA 117(29): 16961-16968 (2020)
• 
  Biswanath Chowdhury, Gautam Garai:
  A bi-objective function optimization approach for multiple sequence alignment using genetic algorithm. Soft Comput. 24(20): 15871-15888 (2020)
• 
  Weidong Yang, Jiangtao Peng, Weiwei Sun:
  Ideal Regularized Discriminative Multiple Kernel Subspace Alignment for Domain Adaptation in Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 5833-5846 (2020)
• 
  Ehsan Kazemi, Matthias Grossglauser:
  MPGM: Scalable and Accurate Multiple Network Alignment. IEEE ACM Trans. Comput. Biol. Bioinform. 17(6): 2040-2052 (2020)
• 
  Mohammed Kayed, Ahmed A. Elngar:
  NestMSA: a new multiple sequence alignment algorithm. J. Supercomput. 76(11): 9168-9188 (2020)
• 
  Vladislav Golyanik, Soshi Shimada, Christian Theobalt:
  Fast Simultaneous Gravitational Alignment of Multiple Point Sets. 3DV 2020: 91-100
• 
  Hugues Thomas:
  Rotation-Invariant Point Convolution With Multiple Equivariant Alignments. 3DV 2020: 504-513
• 
  Songlei Jian, Liang Hu, Longbing Cao, Kai Lu:
  Representation Learning with Multiple Lipschitz-Constrained Alignments on Partially-Labeled Cross-Domain Data. AAAI 2020: 4320-4327
• 
  Mengmeng Kuang, Hing-Fung Ting:
  A data-centric pipeline using convolutional neural network to select better multiple sequence alignment method. BCB 2020: 72:1

skipping 1,264 more matches