Nai-Yang Deng

What is he best known for?

The fields of study Nai-Yang Deng is best known for:

• Drug discovery
• Gene
• DNA

Nai-Yang Deng merges Support vector machine with Structural risk minimization in his research. Nai-Yang Deng applies his multidisciplinary studies on Structural risk minimization and Support vector machine in his research. His study brings together the fields of Consistency (knowledge bases) and Artificial intelligence. His Pseudo amino acid composition research extends to the thematically linked field of Gene. His study in Dipeptide extends to Pseudo amino acid composition with its themes. His work often combines Dipeptide and Amino acid studies. Amino acid and Nucleic acid are two areas of study in which he engages in interdisciplinary research. He merges many fields, such as Nucleic acid and RNA, in his writings. He performs multidisciplinary study in RNA and RNA-binding protein in his work.

His most cited work include:

• Support Vector Machines (136 citations)
• Drug Repositioning by Kernel-Based Integration of Molecular Structure, Molecular Activity, and Phenotype Data (102 citations)
• Predicting DNA- and RNA-binding proteins from sequences with kernel methods (63 citations)

What are the main themes of his work throughout his whole career to date

Artificial intelligence is frequently linked to Class (philosophy) in his study. Nai-Yang Deng combines Support vector machine and Relevance vector machine in his research. He incorporates Relevance vector machine and Structured support vector machine in his research. While working in this field, Nai-Yang Deng studies both Structured support vector machine and Support vector machine. Pattern recognition (psychology) is closely attributed to Artificial intelligence in his work. Machine learning and Computational Science and Engineering are frequently intertwined in his study. In most of his Computational Science and Engineering studies, his work intersects topics such as Machine learning. Nai-Yang Deng merges many fields, such as Algorithm and Operating system, in his writings. Borrowing concepts from Algorithm, he weaves in ideas under Operating system.

Nai-Yang Deng most often published in these fields:

• Artificial intelligence (86.96%)
• Support vector machine (56.52%)
• Pattern recognition (psychology) (52.17%)

What were the highlights of his more recent work (between 2014-2020)?

• Pattern recognition (psychology) (100.00%)
• Artificial intelligence (100.00%)
• Linguistics (50.00%)

In recent works Nai-Yang Deng was focusing on the following fields of study:

His Artificial intelligence research spans across into fields like Data mining and Computer vision. He connects Computer vision with Artificial intelligence in his research. His work in Linguistics is not limited to one particular discipline; it also encompasses Feature (linguistics). His study connects Linguistics and Feature (linguistics). In his research, Nai-Yang Deng undertakes multidisciplinary study on Extraction (chemistry) and Chromatography. Nai-Yang Deng undertakes multidisciplinary investigations into Chromatography and Extraction (chemistry) in his work. His Mechanical engineering study often links to related topics such as Manifold (fluid mechanics). His Manifold (fluid mechanics) study frequently draws connections between related disciplines such as Mechanical engineering. His study deals with a combination of Remote sensing and Hyperspectral imaging.

Between 2014 and 2020, his most popular works were:

• Collaborative Discriminative Manifold Embedding for Hyperspectral Imagery (16 citations)
• Collaborative weighted multi-view feature extraction (9 citations)

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