Srinivasan Ramachandran

Bio: Srinivasan Ramachandran is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: Strongyloides stercoralis & Bacterial adhesin. The author has an hindex of 22, co-authored 36 publications receiving 1645 citations. Previous affiliations of Srinivasan Ramachandran include Jawaharlal Nehru University & Academy of Scientific and Innovative Research.

Prediction of probable genes by Fourier analysis of genomic sequences

Abstract: Motivation: The major signal in coding regions of genomic sequences is a three-base periodicity. Our aim is to use Fourier techniques to analyse this periodicity, and thereby to develop a tool to recognize coding regions in genomic DNA. Result: The three-base periodicity in the nucleotide arrangement is evidenced as a sharp peak at frequency f — 1/3 in the Fourier (or power) spectrum. From extensive spectral analysis of DNA sequences of total length over 5.5 million base pairs from a wide variety or organisms (including the human genome), and by separately examining coding and non-coding sequences, we find that the relative height of the peak at f = 1/3 in the Fourier spectrum is a good discriminator of coding potential. This feature is utilized by us to detect probable coding regions in DNA sequences, by examining the local signal-to-noise ratio of the peak within a sliding window. While the overall accuracy is comparable to that of other techniques currently in use, the measure that is presently proposed is independent of training sets or existing database information, and can thus find general application. Availability: A computer program GeneScan which locates coding open reading frames and exonic regions in genomic sequences has been developed, and is available on request. Contact: E-mail: rama@jnuniv.emet.in.

SPAAN: a software program for prediction of adhesins and adhesin-like proteins using neural networks

Abstract: Motivation: The adhesion of microbial pathogens to host cells is mediated by adhesins. Experimental methods used for characterizing adhesins are time-consuming and demand large resources. The availability of specialized software can rapidly aid experimenters in simplifying this problem. We have employed 105 compositional properties and artificial neural networks to develop SPAAN, which predicts the probability of a protein being an adhesin (Pad). Results: SPAAN had optimal sensitivity of 89% and specificity of 100% on a defined test set and could identify 97.4% of known adhesins at high Pad value from a wide range of bacteria. Furthermore, SPAAN facilitated improved annotation of several proteins as adhesins. Novel adhesins were identified in 17 pathogenic organisms causing diseases in humans and plants. In the severe acute respiratory syndrome (SARS) associated human corona virus, the spike glycoprotein and nsps (nsp2, nsp5, nsp6 and nsp7) were identified as having adhesin-like characteristics. These results offer new lead for rapid experimental testing. Availability: SPAAN is freely available through ftp://203.195.151.45 Contact: [email protected]

A draft map of the human proteome

Abstract: The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.

Diagnosis of Strongyloides stercoralis Infection

Abstract: Strongyloides stercoralis infects 30 million people in 70 countries. Infection usually results in asymptomatic chronic disease of the gut, which can remain undetected for decades. However, in patients receiving long-term corticosteroid therapy, hyperinfection can occur, resulting in high mortality rates (up to 87%). Strongyloidiasis is difficult to diagnose because the parasite load is low and the larval output is irregular. Results of a single stool examination by use of conventional techniques fail to detect larvae in up to 70% of cases. Several immunodiagnostic assays have been found ineffective in detecting disseminated infections and show extensive cross-reactivity with hookworms, filariae, and schistosomes. Although it is important to detect latent S. stercoralis infections before administering chemotherapy or before the onset of immunosuppression in patients at risk, a specific and sensitive diagnostic test is lacking. This review describes the clinical manifestations of strongyloidiasis, as well as various diagnostic tests and treatment strategies.