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In many cases, crucial genes show relatively slight changes between groups of samples (e.g. normal vs. disease), and many genes selected from microarray differential analysis by measuring the expression level statistically are also poorly annotated and lack of biological significance. In this paper, we present an innovative approach - network expansion and pathway enrichment analysis (NEPEA) for integrative microarray analysis. We assume that organized knowledge will help microarray data analysis in significant ways, and the organized knowledge could be represented as molecular interaction networks or biological pathways. Based on this hypothesis, we develop the NEPEA framework based on network expansion from the human annotated and predicted protein interaction (HAPPI) database, and pathway enrichment from the human pathway database (HPD). We use a recently-published microarray dataset (GSE24215) related to insulin resistance and type 2 diabetes (T2D) as case study, since this study provided a thorough experimental validation for both genes and pathways identified computationally from classical microarray analysis and pathway analysis. We perform our NEPEA analysis for this dataset based on the results from the classical microarray analysis to identify biologically significant genes and pathways. Our findings are not only consistent with the original findings mostly, but also obtained more supports from other literatures.

The present study aims to assess the socioecological vulnerability of smallholders through an index of Tehri Garhwal Himalaya. The index provides a realistic approach to recognize the contributions of social and ecological factors for household welfare vulnerability to climate change. The approach puts forward various indices for each component of vulnerability to climate change - exposure, sensitivity, and adaptive capacity including two more indices: one for overall impact under the exposure of climate change and another for overall vulnerability. The five indices were proposed to assess the vulnerability status of with and without agroforestry practicing households in Himalayan region. These indices are based on 35 indicators (8 for exposure; 12 for sensitivity, 15 for adaptive capacity), selected through inductive approaches. A questionnaire for households was designed for the above aim and was administered to 121 heads of households through face-toface interviews with 77 households practicing agroforestry and 44 without agroforestry. The questionnaire dealt the general household information, and indicators of the vulnerability including the issues related to agroforestry. The results highlight slightly higher adaptive capacity of agroforestry practicing households due to specific contribution of agroforestry. The low contribution of agroforestry among smallholders was due to small land holding. The study also results that remoteness, specific issues of smallholders’ such as poverty, education and employment are responsible for the present condition. In particular this study clearly shows that poverty is the key driver for vulnerability. All of these issues can be addressed if future programs and policies, include and implement regulations to remedy attributive factors. This paper may be applicable to other mountainous regions providing insights for effective adaptation strategies to climate change.