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Biomedical Informatics for Cancer Research
view, showing that multiple molecular pathways must be affected for cancer to develop, but with different specific proteins in each pathway mutated or differentially expressed in a given tumor (The Cancer Genome Atlas Research Network 2008; Parsons et al. 2008). Different studies demonstrated that while widespread mutations exist in cancer, not all mutations drive cancer development (Lin et al. 2007). This suggests a need to target only a deleterious subset of aberrant proteins, since any tre- ment must aim to improve health to justify its potential side effects. Treatment for cancer must become highly individualized, focusing on the specific aberrant driver proteins in an individual. This d...
Plant Functional Genomics
Functional genomics is a young discipline whose origin can be traced back to the late 1980s and early 1990s, when molecular tools became available to determine the cellular functions of genes. Today, functional genomics is p- ceived as the analysis, often large-scale, that bridges the structure and organi- tion of genomes and the assessment of gene function. The completion in 2000 of the genome sequence of Arabidopsis thaliana has created a number of new and exciting challenges in plant functional genomics. The immediate task for the plant biology community is to establish the functions of the approximately 25,000 genes present in this model plant. One major issue that will remain even after...
Gene Function Analysis
With the advent of high-throughput technologies following completion of the human genome project and similar projects, the number of genes of interest has expanded and the traditional methods for gene function analysis cannot achieve the throughput necessary for large-scale exploration. This book brings together a number of recently developed techniques for looking at gene function, including computational, biochemical and biological methods and protocols.
Personalized and Precision Medicine Informatics
This book adopts an integrated and workflow-based treatment of the field of personalized and precision medicine (PPM). Outlined within are established, proven and mature workflows as well as emerging and highly-promising opportunities for development. Each workflow is reviewed in terms of its operation and how they are enabled by a multitude of informatics methods and infrastructures. The book goes on to describe which parts are crucial to discovery and which are essential to delivery and how each of these interface and feed into one-another. Personalized and Precision Medicine Informatics provides a comprehensive review of the integrative as well as interpretive nature of the topic and brings together a large body of literature to define the topic and ensure that this is the key reference for the topic. It is an unique contribution that is positioned to be an essential guide for both PPM experts and non-experts, and for both informatics and non-informatics professionals.
Non-coding RNAs and Cancer
The discovery of microRNAs and its role as gene expression regulators in human carcinogenesis represents one of the most important scientific achievements of the last decade. More recently, other non-coding RNAs have been discovered and its implications in cancer are emerging as well, suggesting a broader than anticipated involvement of the non-coding genome in cancer. Moreover, completely new and unexpected functions for microRNAs are being revealed, leading to the identification of new anticancer molecular targets. This book represents a comprehensive guide on non-coding RNAs and cancer, spanning from its role as cancer biomarkers, to providing the most useful bioinformatic tools, to presenting some of the most relevant discoveries, which indicates how these fascinating molecules act as fine orchestrators of cancer biology.
Cancer Research
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Genome Research
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Representation Learning for Natural Language Processing
This book provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based lin...
