RESUMO
Breast cancer is considered to be happened due to genetic aberration. Out of several genes expressed, it is found that cadherin 1, type 1 (CDH1) is responsible in several ways to control the metabolic order in human. Deregulation of the function of protein E-cadherin, expressed from CDH1 plays an important role in lobular breast cancer. In order to understand the root cause of this recent claim, we focus on CDH1 gene: whether the genetic information translated due to any deviation/alteration/modification in its sequence is related to the occurrence of the different types breast cancer. Towards this end, quantitative analysis of different biophysical and bio-chemical properties of CDH1 gene in genomic and proteomic levels from the available genomic (cDNA) sequences of CDH1 gene (obtained from the COSMIC Database for 78 patients, suffering from various types of breast cancer) clearly emphasizes that alternation/modification in the sequence of the CDH1 gene can be detrimental. Furthermore, Random forest, K-nearest neighbour and stochastic gradient descent (SGD) algorithms are applied on the derived dataset to classify the types of breast cancer, and to validate our hypothesis regarding the acute role of CDH1 as potential bio marker for breast cancer. Analysis of the mutated CDH1 gene sequences, and their related parameters using aforesaid machine learning techniques clearly establish that CDH1 gene can take the deterministic role in predicting the chances of occurrences of different types of breast cancer with an accuracy of >90%. Such an observation opens a new paradigm in diagnostic approach of breast cancer.Communicated by Ramaswamy H. Sarma.
RESUMO
As 20 naturally occurring amino acids are coded by 61 mRNA codons out of 64, it is obvious that 61â20 cannot have one-to-one mapping which generates the problem of codon degeneracy. Despite several efforts there is no specific outcome which can describe this well-known enigmatic degeneracy of the codon table. Since, every biological behaviour is regulated by protein which in turn consists of amino acids bearing the inherent characteristics of degeneracy among mRNA codons (Crick F.H.C. The Origin of the Genetic Code. J. Mol. Biol.1968; 38: 367-379), it is worthy to analyse the impact of such degeneracy on biological behaviours. Here, based on mathematical models using the concept of b-type of the nucleotide bases and hamming distances, an effort has been initiated to understand the impact of biasness of genetic code degeneracy on biological behaviours. The proposed models have been utilized to understand the characteristic features of bacterial genes of gram-positive and gram-negative bacteria. To the best of our knowledge, this is the first mathematical model to capture the effect of genetic code degeneracy, showing a paradigm towards understanding the behavioural difference between gram-positive and gram-negative bacteria, and thereby opening a new avenue for revealing differential biological properties.Communicated by Ramaswamy H. Sarma.
RESUMO
The base compositional correlations that hold among various coding and noncoding regions of the canine genome have been analysed. The distribution pattern of genes, on the basis of GC(3) composition, shows a wide range similar to that observed in human. However the occurrence of maximum number of genes was observed in the range of 65-75% of GC(3) composition. The correlation between the coding DNA sequences of canine with the different noncoding regions (introns and flanking regions) is found to be significant and in many cases the degree of correlation show similarity to human genome. We found that these correlations are not limited to the GC content alone, but is holding at the level of the frequency of individual bases as well. The present study suggests that canines ideally belong to the predicted 'general mammalian pattern' of genome composition along with human beings.