The ongoing boom of applications for artificial intelligence (AI) is based on algorithms that were inspired by neuroscience discoveries in the 1960s. This is a timely book to introduce the new discoveries and ideas in neuroscience, for the next wave of more powerful AI. AI researchers are all interested in the human brain, which is more capable and energy-efficient, but do not have good reading materials from the rather separate subfields of neuroscience, all with plenty of jargons. Based on hundreds of publications from top journals, the book fills in the gap between existing computational hardware/algorithms and emerging knowledge from neuroscience.
Investigating Human Diseases with the Microbiome: Metagenomics Bench to Bedside is a summary of underlying principles for human health and disease studies from a microbiome point-of-view. From birth to old age, microbiomes in fecal, oral/nasal, vaginal, and skin samples contain important information that can predict disease risks in the future. Tissue samples also contain microbes that are relevant for diseases. The microbiome connects genetic and environmental factors and is poised to greatly facilitate precision medicine, including prevention, diagnosis and effective treatment of many complex diseases. Based in traditional microbiology and adding a more wholistic view of the advent of high-throughput sequencing, this reference poses the key questions of the total number of microbial cells and their distribution in the human body while also considering concepts from macroecology and from causal reasoning. An entire chapter is dedicated to methods, providing hands-on information for important considerations when collecting samples for metagenomic studies. - Provides a consistent framework for the study of the microbiome at various body sites based on over 10 years of human microbiome studies - Consolidates relevant information for readers looking to get an idea of microbes for human health, elucidating why one might want to include the study of the microbiome in current or future research efforts - Provides technical considerations for designing and carrying out microbiome research and applications
Investigating Human Diseases with the Microbiome: Metagenomics Bench to Bedside is a summary of underlying principles for human health and disease studies from a microbiome point-of-view. From birth to old age, microbiomes in fecal, oral/nasal, vaginal, and skin samples contain important information that can predict disease risks in the future. Tissue samples also contain microbes that are relevant for diseases. The microbiome connects genetic and environmental factors and is poised to greatly facilitate precision medicine, including prevention, diagnosis and effective treatment of many complex diseases. Based in traditional microbiology and adding a more wholistic view of the advent of high-throughput sequencing, this reference poses the key questions of the total number of microbial cells and their distribution in the human body while also considering concepts from macroecology and from causal reasoning. An entire chapter is dedicated to methods, providing hands-on information for important considerations when collecting samples for metagenomic studies. - Provides a consistent framework for the study of the microbiome at various body sites based on over 10 years of human microbiome studies - Consolidates relevant information for readers looking to get an idea of microbes for human health, elucidating why one might want to include the study of the microbiome in current or future research efforts - Provides technical considerations for designing and carrying out microbiome research and applications
The ongoing boom of applications for artificial intelligence (AI) is based on algorithms that were inspired by neuroscience discoveries in the 1960s. This is a timely book to introduce the new discoveries and ideas in neuroscience, for the next wave of more powerful AI. AI researchers are all interested in the human brain, which is more capable and energy-efficient, but do not have good reading materials from the rather separate subfields of neuroscience, all with plenty of jargons. Based on hundreds of publications from top journals, the book fills in the gap between existing computational hardware/algorithms and emerging knowledge from neuroscience.
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