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Problems Faced by All Today

Food based ailments: A global threat

Are you suffering from food poisioning?
While you might encounter thousands of types of bacteria in your everyday environment, most cause you no harm. But when harmful bacteria, such as salmonella, campylobacter, listeria and E. coli, enter our food or water supply, they cause problems ranging from flu-like symptoms to serious illness, even death.Read More

A platform for 24x7 Guidance: Wishlist?

Are we eating to live, or living to eat?
Food is the most complex issue. The growing, hunting, gathering, and obtaining of food are not tasks that most people, with the exception of farmers. Instead our food appears on the shelves of nearby supermarkets, and restaurants. The variety of food displayed and accessible is astounding at times, but we aren't aware of what should be eaten..Read More

Need of an Organic/Natural Supply Chain

From soil to foil
The organic food market has grown, the price of organic foodstuffs remains largely out of the reach of many. A recent study of food access found that a full 49 million people make food decisions based solely on the price of the food. With most organic foods remaining more expensive than conventionally produced food, peope aren't even considering organic food. Organics cost consumers more because the food is distributed under an inefficient distribution network..Read More

Lack of a Collaborative Wellness Ecosystem

Health is Wealth!
A healthy society demands healthy people. To be healthy, people need to be conscious about their health, diet and ecosystem they are in.
Some people are ignorant about their health. Busy schedules force people to compromise with their healthy habits on a regular basis. Sometimes what people need, is simply a little push. Wellness ecosystem will give them an opportunity to explore more about healthy diet, dieticians, nutritionists etc..Read More

RiteFood : The Solution

Personalized Recommendations

Get recommendations regarding what to eat and what to avoid based on the genomic and AI analysis.
• Artificial Intelligence   • Genomics   • Personalized Diet Plan  

Expert Connect

Get help from experts in diet and nutrition.
• Experienced Nutritionists/Dietitians  • Real-time Recommendation  

Wellness Forum

Educate yourself on food and nutrition while sharing your knowledge.
• Learn   • Share   • Grow  

Organic/Natural Aggregator

Get easy access to the best quality organic food sold by verified vendors
• Easy Shopping   • Hgh-Quality Food   • Variety  

Research Work

Fusion of expression values and protein interaction information using multi-objective optimization for improving gene clustering.

One of the crucial problems in the field of functional genomics is to identify a set of genes which are responsible for a particular cellular mechanism. The current work explores the usage of a multi-objective optimization based genetic clustering technique to classify genes into groups with respect to their functional similarities and biological relevance. Our contribution is two-fold: firstly a new quality measure to compute the goodness of gene-clusters namely protein-protein interaction confidence score is developed. This utilizes the confidence scores of the protein-protein interaction networks to measure the similarity between genes of a particular cluster with respect to their biochemical protein products. Continue reading

Graph-based Hub Gene Selection Technique using Protein Interaction Information: Application to Sample Classification

Classification of samples of gene expression profile plays a significant role in prediction and diagnosis of diseases. In the task of sample classification, a robust feature selection algorithm is very much essential to identify the important genes from the high dimensional gene expression data. This paper explores the information of protein-protein interaction (PPI) with a graph mining technique for finding a proper subset of features (genes), which further takes part in sample classification. Here, our contribution for feature selection is three-fold: first, all the genes are grouped into different clusters based on the integrated information of the gene expression values and their protein interactions using a multi-objective optimization (MOO) based clustering approach. Continue reading

Ensembling of Gene Clusters utilizing Deep Learning and Protein-protein Interaction Information

Cluster ensemble techniques aim to combine the outputs of multiple clustering algorithms to obtain a single consensus partitioning. The current paper reports about the development of a cluster ensemble based technique combining the concepts of multiobjective optimization and deep-learning models for gene clustering where some additional protein-protein interaction information are utilized for generating the consensus partitioning. The first approach is based on a traditional machine learning method, and another approach exploits the graph partitioning algorithm and two deep neural models to generate the final clustering.Continue reading

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