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Bottom-up proteomics

Known as: Bottom-up 
Bottom-up proteomics is a common method to identify proteins and characterize their amino acid sequences and post-translational modifications by… 
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Related topics

Related topics

2 relations

Broader (1)

Bioinformatics
Proteomics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2013
Highly Cited
2013
Saliency Detection via Graph-Based Manifold Ranking
Most existing bottom-up methods measure the foreground saliency of a pixel or region based on its contrast within a local context… 
Highly Cited
2009
Highly Cited
2009
Learning to predict where humans look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a… 
Highly Cited
2009
Highly Cited
2009
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling… 
Highly Cited
2005
Highly Cited
2005
A Multilevel Model of Resistance to Information Technology Implementation
To better explain resistance to information technology implementation, we used a multilevel, longitudinal approach. We first… 
Highly Cited
2000
Highly Cited
2000
A Bayesian Computer Vision System for Modeling Human Interactions
We describe a real-time computer vision and machine learning system for modeling and recognizing human behaviors in a visual… 
Highly Cited
1994
Highly Cited
1994
Genetic Programming II: Automatic Discovery of Reusable Programs.
Reading Genetic Programming IE Automatic Discovery ofReusable Programs (GPII) in its entirety is not a task for the weak-willed… 
Highly Cited
1993
Highly Cited
1993
Magnetic bistability in a metal-ion cluster
MAGNETIC materials of mesoscopic dimensions (a few to many thousands of atoms) may exhibit novel and useful properties such as… 
Highly Cited
1987
Highly Cited
1987
Three-Dimensional Object Recognition from Single Two-Dimensional Images
  • D. Lowe
  • Artificial Intelligence
  • 1987
  • Corpus ID: 678619
Highly Cited
1987
Highly Cited
1987
Competitive Learning: From Interactive Activation to Adaptive Resonance
Functional and mechanistic comparisons are made between several network models of cognitive processing: competitive learning… 
Highly Cited
1970
Highly Cited
1970
An efficient context-free parsing algorithm
A parsing algorithm which seems to be the most efficient general context-free algorithm known is described. It is similar to both… 
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