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Genet Mol Res. 2014 Jul 4;13(3):5073-87. doi: 10.4238/2014.July.4.23.

Identifying human disease genes: advances in molecular genetics and computational approaches.

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Department of Bioinformatics, Mohammad Ali Jinnah University, Islamabad Expressway, Islamabad, Pakistan.
Atta-ur-Rahman School of Applied Biosciences, National University of Science and Technology, Islamabad, Pakistan.
Health Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad, Pakistan.
Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology, Nonakuri, Purba Medinipur, India.
Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil.
Laboratório de Genética Celular e Molecular, Departamento de Biologia Geral, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil


The human genome project is one of the significant achievements that have provided detailed insight into our genetic legacy. During the last two decades, biomedical investigations have gathered a considerable body of evidence by detecting more than 2000 disease genes. Despite the imperative advances in the genetic understanding of various diseases, the pathogenesis of many others remains obscure. With recent advances, the laborious methodologies used to identify DNA variations are replaced by direct sequencing of genomic DNA to detect genetic changes. The ability to perform such studies depends equally on the development of high-throughput and economical genotyping methods. Currently, basically for every disease whose origen is still unknown, genetic approaches are available which could be pedigree-dependent or -independent with the capacity to elucidate fundamental disease mechanisms. Computer algorithms and programs for linkage analysis have formed the foundation for many disease gene detection projects, similarly databases of clinical findings have been widely used to support diagnostic decisions in dysmorphology and general human disease. For every disease type, genome sequence variations, particularly single nucleotide polymorphisms are mapped by comparing the genetic makeup of case and control groups. Methods that predict the effects of polymorphisms on protein stability are useful for the identification of possible disease associations, whereas structural effects can be assessed using methods to predict stability changes in proteins using sequence and/or structural information.

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