AN UNSUPERVISED DEEP LEARNING FRAMEWORK FOR PREDICTING HUMAN ESSENTIAL GENES FROM POPULATION AND FUNCTIONAL GENOMIC DATA

An unsupervised deep learning framework for predicting human essential genes from population and functional genomic data

Abstract Background The ability to accurately predict essential genes intolerant to loss-of-function (LOF) mutations can dramatically improve the identification of disease-associated genes.Recently, there have been numerous computational methods developed to predict human essential genes from population genomic data.While the existing methods are h

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A Hierarchical Attention Fused Descriptor for 3D Point Matching

Motivated by recent successes on learning 3D feature representations, we present a Siamese network to generate representative 3D descriptors for 3D point matching in point cloud registration.Our system, dubbed HAF-Net, consists of feature extraction module, hierarchical feature reweighting and recalibration module (HRR), as well as feature aggregat

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EFFECT OF LONGITUDINAL SLOPE ANGLES, VIBRATION SPEEDS AND OUTLETS FOR THE PRODUCE IN GRADING, SEPARATOR OF WHEAT SEED BY USING SPECIFIC GRAVITY SEPARATOR LOCALLY MANUFACTURE

In this study a specific gravity separator has been used in order to consider the effect of three levels of: longitudinal slop angles, vibration speeds, outlets for the produce W Sandals and their effect on specific weight, productivity and seed purity.The results show the longitudinal horizontal slop angle (0) surpassed significantly in recording

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