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Alzheimer's disease (AD) is an age-related disorder characterised by the degeneration of neurons, which leads to cognitive function. Recent research on the genetic basis of AD found some evidence of the potential implication of several risk genes in AD. ...

Drug resistance threatens the effectiveness of treatments of infectious diseases, particularly on the global scale where mutation is rapid, mechanisms of resistance are developing or unknown, and limited data is available. Pathway activity inference is ...

In the past decade, the use of high-throughput sequencing assays has allowed researchers to experimentally acquire thousands of functional measurements for each basepair in the human genome. Despite their value, these measurements are only a small ...

Recent large-scale efforts to characterize functional activity in human have produced thousands of genome-wide experiments that quantify various forms of biochemistry, such as histone modifications, protein binding, transcription, and chromatin ...

The past decade has seen a revolution in genomic technologies that enable a flood of genome-wide profiling of many molecular elements on human genomes. This massive-scale "-omics" data provides researchers with an unprecedented opportunity to understand ...

The coordination of functional genomics is a critical and complex process in biological systems, especially across different phenotypes or organism states (e.g., time, disease, organism). Understanding how the interactions of various genomic functions ...

The issues of privacy and disclosure are two sides of a weighty coin. Computational biologists and other scientists involved in genomic research need to be constantly cognizant of the push and pull of these two important concepts. Clinical genomics ...

Integrative systems biology approaches build, evaluate, and combine data from thousands of diverse experiments. These strategies rely on methods that effectively identify and summarize gene-gene relationships within individual experiments. For gene-...

Comparing the binding sites of proteins is effective for predicting protein functions based on their structure information. However, it is still very challenging to predict the binding ligands from the atomic structures of protein binding sites. In this ...

Gene array experiments are progressively conducted. However, the biological functional interpretation has not kept pace with this rapid escalation. Functional genomics using data mining methods potentially offers precise, objective, and more reliable ...

The following topics are dealt with: computational structural bioinformatics; biomedicine; machine learning; data mining; biomarker discovery; functional genomics; graph techniques; NLP system and health care.

Stability-based methods have been successfully applied in functional genomics to the analysis of the reliability of clusterings characterised by a relatively low number of examples and clusters. The application of these methods to the validation of gene ...

Functions of a protein are mainly determined by its structure. Surface cavities, also called pockets or clefts, are ordinarily regarded as potentially active sites where the protein carries out the functions. Clustering these pockets is a challenging ...

This paper considers the multilabel classification problem, which is a generalization of traditional two-class or multi-class classification problem. In multilabel classification a set of labels categories is given and each training instance is ...

One of the central problems in functional genomics is to establish the classification schemes of protein structures. In this paper the relationship of protein structures is uncovered within the framework of supervised learning. Specifically, the novel ...

In multilabel learning, each instance in the training set is associated with a set of labels and the task is to output a label set whose size is unknown a priori for each unseen instance. In this paper, this problem is addressed in the way that a neural ...

Recent strives in the developing field of functional genomics calls for computerized systems that are capable of providing accurate quantitative data for researchers in biology and genetics. In a current research, the biologists are interested in ...

We present an application of BioDCV, a computational environment for semisupervised profiling with Support Vector Machines, aimed at detecting outliers and deriving informative subtypes of patients with respect to pathological features. First, a sample-...

The purpose of this document is to provide readers with a resource of different ongoing standardization efforts within the ‘omics’ (genomic, proteomics, metabolomics) and related communities, with particular focus on toxicological and environmental ...

A major challenge in the post-genome era of plant biology is to determine the functions of all the genes in the plant genome. A straightforward approach to this problem is to reduce or knock out expression of a gene with the hope of seeing a phenotype ...