In silico analysis for the presence of HARDY an Arabidopsis drought tolerance DNA binding transcription factor product in chromosome 6 of Sorghum bicolor genome

Expression of the Arabidopsis HARDY (hrd) DNA binding transcription factor (555 bp present on chromosome 2) has been shown to increase WUE in rice by Karaba et al 2007 (PNAS, 104:15270–15275). We conducted a detail analysis of the complete sorghum genome for the similarity/presence of either DNA, mRNA or protein product of the Arabidopsis HARDY (hrd) DNA binding transcription factor (555 bp present on chromosome 2). Chromosome 6 showed a sequence match of 61.5 percent positive between 61 and 255 mRNA residues of the query region. Further confirmation was obtained by TBLASTN which showed that chromosome 6 of the sorghum genome has a region between 54948120 and 54948668 which has 80 amino acid similarities out of the 185 residues. A homology model was constructed and verified using Anolea, Gromos and Verify3D. Scanning the motif for possible activation sites revealed that there was a protein kinase C phosphorylation site between 15th and 20th residue. The study indicates the possibility of the presence of a DNA binding transcription factor in chromosome 6 of Sorghum bicolor with 60 percent similarity to that of Arabidopsis hrd DNA binding transcription factor

Iso-geometric Integral Equation Solvers and their Compression via Manifold Harmonics

The state of art of electromagnetic integral equations has seen significant growth over the past few decades, overcoming some of the fundamental bottlenecks: computational complexity, low frequency and dense discretization breakdown, preconditioning, and so on. Likewise, the community has seen extensive investment in development of methods for higher order analysis, in both geometry and physics. Unfortunately, these standard geometric descriptors are $C^0$ at the boundary between patches with a few exceptions; as a result, one needs to define additional mathematical infrastructure to define physical basis sets for vector problems. In stark contrast, the geometric representation used for design is higher-order differentiable over the entire surface. Geometric descriptions that have $C^{2}$-continuity almost everywhere on the surfaces are common in computer graphics. Using these description for analysis opens the door to several possibilities, and is the area we explore in this paper. Our focus is on Loop subdivision based isogeometric methods. In this paper, our goals are two fold: (i) development of computational infrastructure necessary to effect efficient methods for isogeometric analysis of electrically large simply connected objects, and (ii) to introduce the notion of manifold harmonics transforms and its utility in computational electromagnetics. Several results highlighting the efficacy of these two methods are presented

Gene Fusion Markup Language: a prototype for exchanging gene fusion data

Abstract Background An avalanche of next generation sequencing (NGS) studies has generated an unprecedented amount of genomic structural variation data. These studies have also identified many novel gene fusion candidates with more detailed resolution than previously achieved. However, in the excitement and necessity of publishing the observations from this recently developed cutting-edge technology, no community standardization approach has arisen to organize and represent the data with the essential attributes in an interchangeable manner. As transcriptome studies have been widely used for gene fusion discoveries, the current non-standard mode of data representation could potentially impede data accessibility, critical analyses, and further discoveries in the near future. Results Here we propose a prototype, Gene Fusion Markup Language (GFML) as an initiative to provide a standard format for organizing and representing the significant features of gene fusion data. GFML will offer the advantage of representing the data in a machine-readable format to enable data exchange, automated analysis interpretation, and independent verification. As this database-independent exchange initiative evolves it will further facilitate the formation of related databases, repositories, and analysis tools. The GFML prototype is made available at http://code.google.com/p/gfml-prototype/ . Conclusion The Gene Fusion Markup Language (GFML) presented here could facilitate the development of a standard format for organizing, integrating and representing the significant features of gene fusion data in an inter-operable and query-able fashion that will enable biologically intuitive access to gene fusion findings and expedite functional characterization. A similar model is envisaged for other NGS data analyses.http://deepblue.lib.umich.edu/bitstream/2027.42/112901/1/12859_2011_Article_5754.pd

Landscape of gene fusions in epithelial cancers: seq and ye shall find

Abstract Enabled by high-throughput sequencing approaches, epithelial cancers across a range of tissue types are seen to harbor gene fusions as integral to their landscape of somatic aberrations. Although many gene fusions are found at high frequency in several rare solid cancers, apart from fusions involving the ETS family of transcription factors which have been seen in approximately 50 % of prostate cancers, several other common solid cancers have been shown to harbor recurrent gene fusions at low frequencies. On the other hand, many gene fusions involving oncogenes, such as those encoding ALK, RAF or FGFR kinase families, have been detected across multiple different epithelial carcinomas. Tumor-specific gene fusions can serve as diagnostic biomarkers or help define molecular subtypes of tumors; for example, gene fusions involving oncogenes such as ERG, ETV1, TFE3, NUT, POU5F1, NFIB, PLAG1, and PAX8 are diagnostically useful. Tumors with fusions involving therapeutically targetable genes such as ALK, RET, BRAF, RAF1, FGFR1–4, and NOTCH1–3 have immediate implications for precision medicine across tissue types. Thus, ongoing cancer genomic and transcriptomic analyses for clinical sequencing need to delineate the landscape of gene fusions. Prioritization of potential oncogenic “drivers” from “passenger” fusions, and functional characterization of potentially actionable gene fusions across diverse tissue types, will help translate these findings into clinical applications. Here, we review recent advances in gene fusion discovery and the prospects for medicine.http://deepblue.lib.umich.edu/bitstream/2027.42/116210/1/13073_2015_Article_252.pd

Induction motor’s rotor slot variation measurement using logistic regression

Rotor slots in induction motor expand due to thermal imbalance and create magnetic stress. Magnetic stress is a force that develops on the laminated surface of the rotor due to the curving or stretching magnetic flux. Traditional motor fault detection methods never measure magnetic stress on the rotor; a significant problem frequently arises in the motor. Magnetic stress is proportional to slot size variations in the rotor. High slot size variations on the laminated surface of the rotor lead to more curving and stretching magnetic flux and damage the rotor and stator, reducing their efficiency and induce harmonics. In this paper, the Average rotor Slot Size Variation (ASSV) in the rotor is predicted during the running condition of the motor through logistic regression. Logistic regression predicts ASSV by multimodal sensor signal sub-band energy values and measures rotor slot sizes from microscope images. Multimodal sensor signal is obtained from various sensors, such as vibration, temperature, current and Giant Magneto Resistance (GMR). Signal sub-band energy is obtained from Over complete Rational-Dilation Wavelet Transform (ORaDWT). From experimental results, ASSV is more than 75% from standard size, damaging the rotor and stator. The accuracy of ASSV prediction is about 92%