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Biomedical subjects

B D Kulkarni

Publications and source records attributed to B D Kulkarni.

At least 19 recordsLinked to original sources
PubMed2002

Analysis of DNA curvature distribution in mycobacterial promoters using theoretical models.

In this paper, 125 different mycobacterial promoters are analyzed for their DNA curvature distribution using several di- and tri-nucleotide dependent models of DNA curvature. Different models give similar behavior and therefore qualitative validation of the results. Mycobacterial promoters resembling the E. coli sigma(70) type have almost 81% (85%) sequences having medium and high curvature profiles using dinucleotide-dependent models. Non-E. coli sigma(70) type mycobacterial promoters have comparatively higher percent of low curvature profiles. Very few extended -10 promoters have low curvature profiles. Mycobacterial promoters having A(n)T(m) (n+m > or =3) tract in the upstream region of -35 box and repeated in phase with each other have high curvature profiles. M. smegmatis promoters have high curvature profiles compared to M. tuberculosis promoters.

Base Sequence↗
PubMed2001

Parameter estimation in spatially extended systems: the Karhunen-Lóeve and Galerkin multiple shooting approach.

Parameter estimation for spatiotemporal dynamics for coupled map lattices and continuous time domain systems is shown using a combination of multiple shooting, Karhunen-Loéve decomposition and Galerkin's projection methodologies. The resulting advantages in estimating parameters have been studied and discussed for chaotic and turbulent dynamics using small amounts of data from subsystems, availability of only scalar and noisy time series data, effects of space-time parameter variations, and in the presence of multiple time scales.

Journal Article↗
PubMed2001

Dynamic optimization of chemical processes using ant colony framework.

Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples. This new computational tool is simple to implement and can tackle problems with state as well as terminal constraints in a straightforward fashion. It requires fewer grid points to reach the global optimum at relatively very low computational effort. The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.

Journal Article↗
PubMed2000

ANN modeling of DNA sequences: new strategies using DNA shape code.

Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.

Algorithms↗
PubMed2000

Optimum DNA curvature using a hybrid approach involving an artificial neural network and genetic algorithm.

In the present paper, a hybrid technique involving artificial neural network (ANN) and genetic algorithm (GA) has been proposed for performing modeling and optimization of complex biological systems. In this approach, first an ANN approximates (models) the nonlinear relationship(s) existing between its input and output example data sets. Next, the GA, which is a stochastic optimization technique, searches the input space of the ANN with a view to optimize the ANN output. The efficacy of this formalism has been tested by conducting a case study involving optimization of DNA curvature characterized in terms of the RL value. Using the ANN-GA methodology, a number of sequences possessing high RL values have been obtained and analyzed to verify the existence of features known to be responsible for the occurrence of curvature. A couple of sequences have also been tested experimentally. The experimental results validate qualitatively and also near-quantitatively, the solutions obtained using the hybrid formalism. The ANN-GA technique is a useful tool to obtain, ahead of experimentation, sequences that yield high RL values. The methodology is a general one and can be suitably employed for optimizing any other biological feature.

Algorithms↗
PubMed1998

Analysis of DNA curvature using artificial neural networks.

MOTIVATION: Our aim is to utilize an artificial neural network (ANN) for the prediction of DNA curvature in terms of retardation anomaly. RESULTS: An ANN capturing the role of phasing, increased helix flexibility, run of poly(A) tracts and flanking base pair effects in determining the extent of DNA curvature has been developed. The network predictions validate the known experimental results and also explain how the base pairs other than ApA affect the curvature. The results suggest that ANN can be used as a model-free tool for studying DNA curvature. AVAILABILITY: The optimal weights and the procedure to compute the retardation anomaly value are available on request from the authors. CONTACT: bdk@ems. ncl.res.in

Base Sequence↗
PubMed1996

Theoretical permutation gel electrophoretic analysis of a curved DNA fragment located in circular permutation.

Using the theoretical model for DNA curvature, we analyzed a set of fragments with a curved insert located in circular permutation. The theoretical permutation analysis of each of the cyclically located fragments reveals the presence of a shifting molecular bend locus. The delineation of the molecular bend locus associated with the fragments obtained by a second permutation helps in providing an explanation for the differential mobility behavior of the fragments.

Animals↗
PubMed1995

Differential binding of RNA polymerase to the wild type Mu mom promoter and its C independent mutant: a theoretical analysis.

Using the theoretical model for DNA bending we have analyzed the Mu mom promoter wild type and its mutant tin7 which showed differential binding to the RNA polymerase. We have demonstrated here the structural change as a result of the point mutation which may be responsible for the altered binding of RNA polymerase. Analysis using both sets of parameters essentially gives the same result.

Bacteriophage mu↗
PubMed1995

Analysis of transcription control signals using artificial neural networks.

The role of the upstream region in controlling the transcription efficiency of a gene is well established. However, the question of predicting the extent of gene expressed given the upstream region has so far remained unresolved. Using an artificial neural network (ANN) to capture the internal representation associated with the transcription control signal, the present work predicts the rate of mRNA synthesis based on the pattern contained in the upstream region. Further, the model has been used to predict the transcription efficiency for all possible single base mutations associated with the beta-globin promoter. The simulation results reveal that apart from the experimental observation that alpha-79G-A and -78G-A mutation increases the efficiency of transcription, mutation in these regions by C or T also causes an increase in transcription. Furthermore the simulation results verify that mutations in the conserved region, in general, decrease the transcriptional efficiency. However, the results also show that certain sequence elements, when mutated, either cause a marginal increase in the level of transcription or have no effect on transcription levels. The simulation results can be used as a guide in designing mutation experiments since an a priori estimate of the possible outcome of a mutation can be obtained.

Animals↗
PubMed1994

On the mobility behavior of a curved DNA fragment located in circular permutation.

Experimental and theoretical investigations on the mobility behavior of a set of permuted fragments with a K-DNA insert is reported. The fragments with the permuted flanking sequences have the K-DNA insert located differentially with respect to the fragment ends. The fragment wherein the insert is located in the center showed maximum retardation as compared to fragments where the insert was at the end. The experimental analysis is also in accord with the theoretical investigation.

Base Sequence↗
PubMed1994

Application of artificial neural networks for prokaryotic transcription terminator prediction.

Artificial neural networks (ANN) to predict terminator sequences, based on a feed-forward architecture and trained using the error back propagation technique, have been developed. The network uses two different methods for coding nucleotide sequences. In one the nucleotide bases are coded in binary while the other uses the electron-ion interaction potential values (EIIP) of the nucleotide bases. The latter strategy is new, property based and substantially reduces the network size. The prediction capacity of the artificial neural network using both coding strategies is more than 95%.

DNA↗
PubMed1994

On the consensus structure within the E. coli promoters.

Using the theoretical model of DNA curvature, we have studied about 112 different E. coli promoters with a view to obtain some common super structures associated with them. Out of the 112 promoters analyzed by theoretical gel electrophoresis permutation about 66 of them have their minima lying between the -10 and the -35 region. The analysis of the bases at the minima reveals strong structural similarities. The differences can account for the varying strengths of the promoters as well as for different degree with which the RNA polymerase binds to these regions. The effects of mutation in each of these 112 promoters and their changes in curvature dispersion have also been evaluated.

Consensus Sequence↗
PubMed1981

Plasma estrogens in the assessment of fetoplacental function.

A retrospective study has been undertaken to assess the diagnostic value of plasma estriol (E3) determinations, as compared with determinations of other biochemical parameters, in predicting the outcome of pregnancy. The normal levels of plasma unconjugated and total E3 were determined on weekly samples obtained during the third trimester of 258 normal pregnancies. Weekly concurrent specimens of plasma and 24-hour urine collections were obtained from 17 high-risk pregnancies associated with hypertension, intrauterine growth retardation and diabetes. Determination of plasma unconjugated and total E3 were made along with human placental lactogen (HPL), urinary E3, and other biophysical parameters such as the oxytocin challenge test, non-stressed test, ultrasonography, etc. The results of plasma E3 were not reported nor used for the clinical management of the patient. The data suggests that weekly plasma determinations were of little value in the assessment of feto-placental status. Some observations on the extent of variability of plasma E3 are discussed.

Adult↗