Multi-Class Clustering of Cancer Subtypes through SVM Based Ensemble of Pareto-Optimal Solutions for Gene Marker Identification

With the advancement of microarray technology, it is now possible to study the expression profiles of thousands of genes across different experimental conditions or tissue samples simultaneously. Microarray cancer datasets, organized as samples versus genes fashion, are being used for classification of tissue samples into benign and malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer subtype, which helps in successful diagnosis of particular cancer types. In this article, we have presented an unsupervised cancer classification technique based on multiobjective genetic clustering of the tissue samples. In this regard, a real-coded encoding of the cluster centers is used and cluster compactness and separation are simultaneously optimized. The resultant set of near-Pareto-optimal solutions contains a number of non-dominated solutions. A novel approach to combine the clustering information possessed by the non-dominated solutions through Support Vector Machine (SVM) classifier has been proposed. Final clustering is obtained by consensus among the clusterings yielded by different kernel functions. The performance of the proposed multiobjective clustering method has been compared with that of several other microarray clustering algorithms for three publicly available benchmark cancer datasets. Moreover, statistical significance tests have been conducted to establish the statistical superiority of the proposed clustering method. Furthermore, relevant gene markers have been identified using the clustering result produced by the proposed clustering method and demonstrated visually. Biological relationships among the gene markers are also studied based on gene ontology. The results obtained are found to be promising and can possibly have important impact in the area of unsupervised cancer classification as well as gene marker identification for multiple cancer subtypes

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Not AvailableFive empirical methods (viz. Cuenca, 1989; Snyder, 1992; Orang, 1998; Pereira, 1995 and Allen and Pruit, 1991) were evaluated to find out Kp using daily weather data (temperature, relative humidity and wind speed) of Indian Agricultural Research Institute station over the years 1997 to 2011. It was observed that the measured Kp values showed bi-modal variation during the year with values ranging between 0.72 to 0.93, being lower in the summer months and higher in rainy and winter months. Out of the five methods, Snyder method was found to be the best for estimating Kp with RMSE of 0.05, and MAD of 0.04. The ETo estimated with Kp of Snyder method also showed lowest RMSE of 0.19, and MAD about 0.16. It is recommended that temporal variation in Kp should be computed for each station for estimation of ETo and Snyder method is recommended for estimating Kp in semi-arid environments.Not Availabl

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Not AvailableA field experiment was conducted during kharif season of 2009 and 2010 in a sandy loam soil of New Delhi to study the effect of weather, achieved by sowing at normal (D1) and late (D2), on soil moisture prediction, evapotranspiration (ET), yield and water use efficiency (WUE) of three varieties (V1: JS 335, V2: Pusa 9712 and Pusa 9814) of soybean. Study of soybean phenology showed that there was reduction in the number of days taken for the crop to complete life cycle with delayed sowing. The agrometeorological water balance model could satisfactorily predict soil moisture content during soybean crop growth period with RMSE (%) varying between 6.27 to 12.06 and correlation coefficient between 0.828 to 0.982. The ET decreased significantly with delay in sowing; however there was no significant variation among the varieties. Among the stages of the soybean crop, mid season stage had highest ET followed by development stage, late season stage and initial stage. Normal sowing resulted in higher yield but lower WUE than the late sowing. Among the cultivars, JS 335 resulted in lower yield and WUE than Pusa 9712 and Pusa 9814. It may be recommended that, Pusa 9712 or Pusa 9814 may be sown during first and second week of July (normal sowing) to achieve higher yield in the semi-arid environment of Delhi region.Not Availabl

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Not AvailableThe date of sowing of Indian mustard (Brassica juncea) varies from year to year depending upon the harvesting of previous wet season crop in the northern and north-western part of India, which exposes the mustard crop to variable weather conditions. So an experiment was conducted in Indian Agricultural Research Institute research farm to study the interactive effect of variable weather and cultivars on yield, radiation and water use efficiency of mustard. In this experiment, split plot design was adopted with date of sowing (early, normal and late) as main plot treatment and mustard cultivars (Pusa Gold, Pusa Jai Kisan and Pusa Bold) as subplot treatments. Pooled over the years, mustard seed yield, radiation and water use efficiency was significantly (p = 0.05) lower in late sowing compared to early sowing (by 46, 32 and 40%, respectively) and normal sowing (by 44, 26 and 41%, respectively). Early sowing and normal sowing were statistically at par with respect to mustard seed yield and water use efficiency. Among the cultivars, Pusa Jai Kisan and Pusa Bold were statistically at par with respect to seed yield, radiation and water use efficiency whereas Pusa Gold registered significantly lower seed yield, radiation and water use efficiency compared to the cultivars Pusa Jai Kisan (by 55, 23 and 52%, respectively) and Pusa Bold (by 56, 20 and 54%, respectively). There was significant interaction between date of sowing and cultivars with respect to seed yield, radiation and water use efficiency of mustard. From the above study it was concluded that normal or early sowing of the Pusa Jai Kisan or Pusa Bold cultivar may be practiced for achieving higher seed yield, radiation and water use efficiency in the semi arid environment of north and north-western part of IndiaNot Availabl

Angioplasty of unprotected left main coronary stenosis: Real world experience of a single-operator group from eastern India

AbstractBackgroundCoronary artery bypass graft surgery is the standard treatment of unprotected left main coronary stenosis (ULMCA). However, in the real world scenario, many of these patients are unfit for CABG or prefer angioplasty as an alternative when offered the choice.MethodsA total of 86 clinically stable patients with ULMCA stenosis who were unfit or unwilling for CABG underwent PCI with DES at two tertiary care centers in Kolkata. Patients were followed up prospectively for a median of 34.6 months for major adverse cardiovascular events. Angiographic follow-up was done after 1 year of index procedure or earlier, if indicated.ResultsFifty-five patients (64%) had distal left main stenosis. Two-stent technique was used in 19 patients (22%) and single-stent technique in 36 patients (42%) with distal left main lesion. Thirteen patients (15.1%) had left ventricular ejection fraction (LVEF) of ≤45%. There was no in-hospital death, MI, or stent thrombosis. During follow-up, major adverse cardiac event (MACE) occurred in 9 patients (10.5%). Our study revealed significantly greater MACE in patients with distal left main lesion with LVEF ≤45% (50% vs 6.38%, p=0.0002), high SYNTAX score (36.36% vs 6.82%, p=0.008), and diabetes (17.95% vs 0.00%, p=0.07). Overall, also patients with Diabetes, LVEF ≤ 45%, and SYNTAX score >32 had significantly higher MACE. Use of IC Stent, IVUS, or procedural strategy in distal lesion did not affect MACE.ConclusionIn selective patients with low-intermediate SYNTAX score and without diabetes and LV dysfunction, ULMCA PCI with DES is feasible

Multi-pion production in hadron-nucleus interactions-self—similar or self-affine

398-402<span style="font-size:14.0pt;line-height: 115%;font-family:" times="" new="" roman";mso-fareast-font-family:"times="" roman";="" color:black;mso-ansi-language:en-in;mso-fareast-language:en-in;mso-bidi-language:="" hi"="" lang="EN-IN">Two-dimensional factorial moments analysis of multi-particle production in π¯- AgBr interactions at 350 GeV/c with real phase-space partition is performed by considering anisotropy of phase space. It is observed that multi-particle production process is self-affine rather than self-similar. The importance of two-dimensional analysis for the interpretation of data in terms of intermittency is also demonstrated.</span

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Not AvailableAn attempt was made to identify priority zones of available micronutrients in the soils of agro-ecological subregions (AESR) of north-eastern states of India (Assam, Nagaland, Sikkim and Tripura) using geo-spatial techniques. Surface soil samples (0–25 cm) were collected from Assam (AESRs 15.2, 15.3, 15.4 and 17.1), Nagaland (AESR 17.1), Sikkim (AESR 16.2) and Tripura (AESR 17.2) and analysed for pH, organic carbon and DTPA-extractable micronutrients (Fe, Mn, Zn and Cu) by standard procedures. Regular Spline was employed as spatial interpolation techniques for obtaining spatial distribution of available micronutrients in soils. The AESR map was overlaid on spatial distribution layers to obtain spatial variability of micronutrients in the AESRs of north-eastern regions of India. Zinc deficiency was common in all the AESR. Maximum deficient area of Zn, Mn and Cu was observed in AESR 15.4, and it was regarded as the high-priority zone, whereas AESR 16.2 and AESR 17.2 were considered as low-priority zone. Rainfall, pH and organic carbon appeared to be the key factors in controlling micronutrient availability in soils of north-eastern regions of India.Not Availabl

Priority Zoning of Available Micronutrients in the Soils of Agro-ecological Sub-regions of North-East India Using Geo-spatial Techniques

Not AvailableAn attempt was made to identify priority zones of available micronutrients in the soils of agro-ecological subregions (AESR) of north-eastern states of India (Assam, Nagaland, Sikkim and Tripura) using geo-spatial techniques. Surface soil samples (0–25 cm) were collected from Assam (AESRs 15.2, 15.3, 15.4 and 17.1), Nagaland (AESR 17.1), Sikkim (AESR 16.2) and Tripura (AESR 17.2) and analysed for pH, organic carbon and DTPA-extractable micronutrients (Fe, Mn, Zn and Cu) by standard procedures. Regular Spline was employed as spatial interpolation techniques for obtaining spatial distribution of available micronutrients in soils. The AESR map was overlaid on spatial distribution layers to obtain spatial variability of micronutrients in the AESRs of north-eastern regions of India. Zinc deficiency was common in all the AESR. Maximum deficient area of Zn, Mn and Cu was observed in AESR 15.4, and it was regarded as the high-priority zone, whereas AESR 16.2 and AESR 17.2 were considered as low-priority zone. Rainfall, pH and organic carbon appeared to be the key factors in controlling micronutrient availability in soils of north-eastern regions of India.Not Availabl