• 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 23 matches

• 2020
• 
  Chanaka Bulathsinghalage, Lu Liu:
  Network-based method for regions with statistically frequent interchromosomal interactions at single-cell resolution. BMC Bioinform. 21-S(14): 369 (2020)
• 2019
• 
  Saman Amini, Annika Jacobsen, Olga Ivanova, Philip Lijnzaad, Jaap Heringa, Frank C. P. Holstege, K. Anton Feenstra, Patrick Kemmeren:
  The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern. PLoS Comput. Biol. 15(5) (2019)
• 2018
• 
  T. M. G. Tennakoon, Richi Nayak:
  Discovering Influence Hierarchy Based on Frequent Social Interactions. ASONAM 2018: 575-576
• 
  T. M. G. Tennakoon, Richi Nayak:
  A Concise Social Network Representation with Flow Hierarchy Using Frequent Interactions. ICTAI 2018: 631-638
• 2016
• 
  Mihye Seo, Jinhee Kim, Hyeseung Yang:
  Frequent Interaction and Fast Feedback Predict Perceived Social Support: Using Crawled and Self-Reported Data of Facebook Users. J. Comput. Mediat. Commun. 21(4): 282-297 (2016)
• 2015
• 
  Anna Fariha, Chowdhury Farhan Ahmed, Carson K. Leung, Md. Samiullah, Suraiya Pervin, Longbing Cao:
  A new framework for mining frequent interaction patterns from meeting databases. Eng. Appl. Artif. Intell. 45: 103-118 (2015)
• 
  Jérôme Villeneuve, Claude Cadoz, James Leonard:
  Analyse de modèles physiques, modèles physiques d'analyse. Synthèse sonore et analyse fréquentielle à l'aide des réseaux masses-interactions CORDIS-ANIMA. Traitement du Signal 32(4): 365-390 (2015)
• 
  Fei Fang, Peter Stone, Milind Tambe:
  Defender Strategies In Domains Involving Frequent Adversary Interaction. AAMAS 2015: 1663-1664
• 
  Raymond Kang, Josh Radinsky, Leilah Lyons:
  Frequent sequential interactions as opportunities to engage in temporal reasoning with an online GIS. LAK 2015: 408-409
• 2014
• 
  Alex R. Gawronski, Marcel Turcotte:
  RiboFSM: Frequent subgraph mining for the discovery of RNA structures and interactions. BMC Bioinform. 15(S-13): S2 (2014)
• 2013
• 
  Seema Mishra, Gora Chand Nandi:
  Link Mining Using Strength of Frequent Pattern of Interaction. ICACNI 2013: 745-752
• 
  Anna Fariha, Chowdhury Farhan Ahmed, Carson Kai-Sang Leung, S. M. Abdullah, Longbing Cao:
  Mining Frequent Patterns from Human Interactions in Meetings Using Directed Acyclic Graphs. PAKDD (1) 2013: 38-49
• 2012
• 
  Radu-Daniel Vatavu:
  Nomadic gestures: A technique for reusing gesture commands for frequent ambient interactions. J. Ambient Intell. Smart Environ. 4(2): 79-93 (2012)
• 
  Asier Aztiria, Juan Carlos Augusto, Rosa Basagoiti, Alberto Izaguirre, Diane J. Cook:
  Discovering frequent user-environment interactions in intelligent environments. Pers. Ubiquitous Comput. 16(1): 91-103 (2012)
• 
  Yadid Ayzenberg, Javier Hernandez Rivera, Rosalind W. Picard:
  FEEL: frequent EDA and event logging - a mobile social interaction stress monitoring system. CHI Extended Abstracts 2012: 2357-2362
• 
  Pak-Ming Cheung, Kam-Tim Woo:
  MCMC-based human tracking with stereo cameras under frequent interaction and occlusion. CISDA 2012: 1-8
• 2011
• 
  Peipei Li, Lyong Heo, Meijing Li, Keun Ho Ryu, Gouchol Pok:
  Protein function prediction using frequent patterns in protein-protein interaction networks. FSKD 2011: 1616-1620
• 2010
• 
  Sandra García-Blasco, Roxana Dánger, Paolo Rosso:
  Drug-Drug Interaction Detection: A New Approach Based on Maximal Frequent Sequences. Proces. del Leng. Natural 45: 263-266 (2010)
• 
  Young-Rae Cho, Aidong Zhang:
  Predicting protein function by frequent functional association pattern mining in protein interaction networks. IEEE Trans. Inf. Technol. Biomed. 14(1): 30-36 (2010)
• 2008
• 
  Young-Rae Cho, Aidong Zhang:
  Discovering Frequent Patterns of Functional Associations in Protein Interaction Networks for Function Prediction. BIBM 2008: 59-65
• 
  Christine Martin, Antoine Cornuéjols:
  Identifying Interface Elements Implied in Protein-Protein Interactions Using Statistical Tests and Frequent Item Sets. BIBM 2008: 78-83
• 2006
• 
  Dick Ng'ambi:
  Influence of Individual Learning Styles in Online Interaction: a Case for Dynamic Frequently Asked Questions (DFAQ). Education for the 21st Century 2006: 125-134
• 2005
• 
  Xiao Bing Huang, Jian Tang:
  SPL: An Structured Pipeline Method for Frequent Remote Service Interactions in Bioinformatics Workflows. ICWS 2005: 795-796