Topics 

This is the first workshop on Intelligent Computing & Bioinformatics. The workshop primarily aims to promote the research, development and application of advanced intelligent computing and bioinformatics techniques. This workshop has a further aim of increasing the awareness of industry of advanced sophisticated techniques and the economic benefits that can be gained by implementing them.

The intelligent computing techniques include a range of techniques such as artificial intelligence, neural networks, pattern recognition, evolutionary and adaptive computing, bio-inspired computing, fuzzy soft computing, case based and constrained reasoning, agents, networking and computer supported co-operative working, human computer interface issues, etc. With the development of computational biology and bioinformatics, we have witnessed and experienced the emerging power of mathematics and computer science in interpreting the high-throughput biological data, and the cooperation of biologists and computer scientists is now greatly revolutionizing the traditional biological science and even the world.

Our theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research in molecular biology. Only original high quality papers related to this theme are especially solicited, including theories, methodologies, and applications in science and technology. Topics covering industrial issues/applications and academic research into intelligent computing will be included, but not limited to:

[A].  Current status and future research directions of bioinformatics

[B].  The application of intelligent computing to bioinformatics

[C].  Sequence analysis and structural alignment

[D].  Gene finding and algorithm design

[E].   Protein structure prediction

[F].   Molecular evolution and comparative genomics

[G].  Analysis of non-coding region and DNA language

[H].  Systems biology and network biology

[ I ].  Sequence assembly

[J].   Gene determination and analysis of expression profiles

[K].  Design and implementation of gene chips

[L].   Development, management and searching strategies of biological database.

[M]. Identification of linear sequence and motifs

[N]. Genetic mapping and phylogenetics

[O].  Nanobiology and sequencing

[P].  The application of machine learning techniques to the analysis of biological data

[Q].  Biomedical sciences and bioinformatics

[R].  Gene ontology

[S].  Biological data fusion

[T].  Data mining techniques and bioinformatics