ENCODE 3 (2012-2017) expanded production and added new types of assays 8 (Fig. 1, Extended Data Fig. 1), which revealed landscapes of RNA binding and the 3D organization of chromatin via methods such as chromatin interaction analysis by paired-end tagging (ChIA-PET) and Hi-C chromosome conformation capture. Phases 2 and 3 delivered 9,239 experiments (7,495 in human and 1,744 in mouse) in more than 500 cell types and tissues, including mapping of transcribed regions and transcript isoforms, regions of transcripts recognized by RNA-binding proteins, transcription factor binding regions, and regions that harbour specific histone modifications, open chromatin, and 3D chromatin interactions. The results of all of these experiments are available at the ENCODE portal (http://www.encodeproject.org). These efforts, combined with those of related projects and many other laboratories, have produced a greatly enhanced view of the human genome (Fig. 2), identifying 20,225 protein-coding and 37,595 noncoding genes

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Contrastive adversarial domain adaptation for machine remaining useful life prediction.

Identifying the rising stars is an important but difficult human resource exercise in all organizations. Rising stars are those who currently have relatively low profiles but may eventually emerge as prominent contributors to the organizations. In this paper, we propose a novel PubRank algorithm to identify rising stars in research communities by mining the social networks of researchers in terms of their co-authorship relationships. Experimental results show that PubRank algorithm can be used to effectively mine the bibliography networks to search for rising stars in the research communities.