@conference { ISI:000252140200008, title = {Fault diagnosis using dynamic time warping}, booktitle = {Pattern Recognition and Machine Intelligence, Proceedings}, series = {LECTURE NOTES IN COMPUTER SCIENCE}, volume = {4815}, year = {2007}, note = {2nd International Conference on Pattern Recognition and Machine Intelligence, Calcutta, INDIA, DEC 18-22, 2007}, month = {DEC}, pages = {57-66}, publisher = {Indian Stat Inst, Machine Intelligence Univ; ISI Ctr Soft Comp Res; Int Assoc Pattern Recognit; Int Ctr Pure \& Appl Math; Web Intelligence Consortium; Yahoo India Res \& Dev; Philips Res Asia}, organization = {Indian Stat Inst, Machine Intelligence Univ; ISI Ctr Soft Comp Res; Int Assoc Pattern Recognit; Int Ctr Pure \& Appl Math; Web Intelligence Consortium; Yahoo India Res \& Dev; Philips Res Asia}, address = {Heidelberger Platz 3, D-14197 Berlin, Germany}, abstract = {

Owing to the superiority of Dynamic Time Warping as a similarity measure of time series, it can become an effective tool for fault diagnosis in chemical process plants. However, direct application of Dynamic Time Warping can be computationally inefficient, given the complexity involved. In this work we have tackled this problem by employing a warping window constraint and a Lower Bounding measure. A novel methodology for online fault diagnosis with Dynamic Time Warping has been suggested and its performance has been investigated using two simulated case studies.

}, isbn = {978-3-540-77045-9}, issn = {0302-9743}, author = {Rajshekhar and Gupta, Ankur and Samanta, A. N. and Kulkarni, B. D. and Jayaraman, Valadi K.}, editor = {Ghosh, A. and De, R. K. and Pal, S. K.} } @conference { ISI:000252140200050, title = {Granular support vector machine based method for prediction of solubility of proteins on overexpression in Escherichia coli}, booktitle = {Pattern Recognition and Machine Intelligence, Proceedings}, series = {LECTURE NOTES IN COMPUTER SCIENCE}, volume = {4815}, year = {2007}, note = {2nd International Conference on Pattern Recognition and Machine Intelligence, Calcutta, INDIA, DEC 18-22, 2007}, month = {DEC}, pages = {406-415}, publisher = {Indian Stat Inst, Machine Intelligence Univ; ISI Ctr Soft Comp Res; Int Assoc Pattern Recognit; Int Ctr Pure \& Appl Math; Web Intelligence Consortium; Yahoo India Res \& Dev; Philips Res Asia}, organization = {Indian Stat Inst, Machine Intelligence Univ; ISI Ctr Soft Comp Res; Int Assoc Pattern Recognit; Int Ctr Pure \& Appl Math; Web Intelligence Consortium; Yahoo India Res \& Dev; Philips Res Asia}, address = {Heidelberger Platz 3, D-14197 Berlin, Germany}, abstract = {

We employed a granular support vector Machines(GSVM) for prediction of soluble proteins on over expression in Escherichia coli. Granular computing splits the feature space into a set of subspaces (or information granules) such as classes, subsets, clusters and intervals [14]. By the principle of divide and conquer it decomposes a. bigger complex problem into smaller and computationally simpler problems. Each of the granules is then solved independently and all the results are aggregated to form the final solution. For the purpose of granulation association rules was employed. The results indicate that a difficult imbalanced classification problem can be successfully solved by employing GSVM.

}, isbn = {978-3-540-77045-9}, issn = {0302-9743}, author = {Kumar, Pankaj and Jayaraman, Valadi K. and Kulkarni, B. D.}, editor = {Ghosh, A. and De, R. K. and Pal, S. K.} } @article { ISI:000341579600004, title = {Coupled cluster methods for autoionisation resonances}, journal = {International Reviews in Physical Chemistry}, volume = {33}, number = {3}, year = {2014}, month = {SEP}, pages = {397-425}, publisher = {TAYLOR \& FRANCIS LTD}, address = {4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND}, abstract = {

The quantum chemical calculation of autoionisation resonances in many-electron systems is a highly challenging task due to the ionisation continuum involved. Recently, advances were reported where conventionally used ab initio codes can be employed to compute autoionisation resonances. This is made possible by the use of analytical continuation tools such as complex scaling and complex absorbing potential (CAP) in the electronic structure codes. We review the formulation and the use of complex scaling and CAP in coupled cluster methods for the electron correlated calculation of energy position and autoionisation decay rate of resonance states. The application of analytically continued coupled cluster method for the correlated calculation of interatomic or intermolecular Coulombic decay process is also discussed.

}, keywords = {autoionisation resonances, complex absorbing potential, complex scaling, equation-of-motion coupled cluster, Fock space multi-reference-coupled cluster, intermolecular Coulombic decay}, issn = {0144-235X}, doi = {10.1080/0144235X.2014.935585}, author = {Sajeev, Y. and Ghosh, A. and Vaval, N. and Pal, S.} } @article {44223, title = {Enhanced and synergistic downregulation of oncogenic miRNAs by self-assembled branched DNA}, journal = {Nanoscale}, volume = {10}, year = {2018}, month = {JAN}, pages = {195-202}, type = {Article}, abstract = {

miRNAs, a group of small non-coding RNA molecules, regulate the expression of many genes involved in various cellular processes. Acute evidence suggests that one miRNA can regulate many genes as its targets, while one gene can be targeted by many miRNAs that co-operatively regulate the gene. Thus, targeting a single miRNA is not sufficient enough to rescue the disease phenotype but it is also essential to target multiple miRNAs simultaneously. This inspired us to design a novel DNA nanostructure that can concurrently downregulate multiple oncomiRNAs. Here we designed a programmable antimiR branched DNA (antimiR-bDNA) nanostructure having antimiRNAs for selective binding to oncomiRNAs miRNA-27a, 96 and 182 which collectively downregulate FOXO1a expression. The antimiR-bDNAs show enhanced stability compared to naked antimiRNAs in serum and are able to knockdown these miRNAs with up to similar to 50\% greater repression as compared to antimiRNAs. This synergistic miRNA repression leads to the restoration of FOXO1a protein levels which in turn inhibit G1-S traversion in cancer cells. To the best of our knowledge, this is the first study harnessing the ability of bDNA structures to silence multiple miRNAs simultaneously.

}, issn = {2040-3364}, doi = {10.1039/c7nr06601e}, author = {Nahar, S. and Nayak, A. K. and Ghosh, A. and Subudhi, U. and Maiti, S.} }