Demand for fisheries products in Brazil

Fish consumption per capita in Brazil is relatively modest when compared to other animal proteins. This study analyses the influence of protein prices, other food prices and population income on the fish demand in Brazil. First, the problem of fish supply in Brazil is characterized. It is followed by reviews of the relevant economic theory and methods of Almost Ideal Demand System - AIDS and their elasticity calculations. A descriptive analysis of fish demand in Brazil using the microdata called "Pesquisa de Orçamento Familiar" (Familiar Budget Research) - POF 2002-2003 is presented. Finally, demand functions and their elasticities are calculated for two different cases: one considering five groups of animal proteins (Chicken; Milk and Eggs; Fish; Processed Proteins and Red Meat) and other with seven groups of food categories (Cereals; Vegetables and Fruits; Milky and Eggs; Oils and Condiments; Fish; Other processed foods; and Meats). The main results are: per capita consumption of fish (4.6 kg per inhabitant per year) is low in Brazil because few households consume fish. When only households with fish consumption are considered, the per capita consumption would be higher: 27.2 kg per inhabitant per year. The fish consumption in the North-East Region is concentrated in the low-income class. In the Center-South Region, the fish consumption is lower and concentrated in the intermediate income classes. The main substitutes for fish are the processed proteins and not the traditional types of meat, such as chicken and red meat

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types