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- Mahdi Shafiei, Hugh Chipman
- 2009

Transactional network data arise in many fields. Although social network models have been applied to transactional data, these models typically assume binary relations between pairs of nodes. We develop a latent mixed membership model capable of modelling richer forms of transactional data. Estimation and inference are accomplished via a variational EM… (More)

Transactional network data can be thought of as a list of one-to-many communications (e.g., email) between nodes in a social network. Most social network models convert this type of data into binary relations between pairs of nodes. We develop a latent mixed membership model capable of modeling richer forms of transactional network data, including relations… (More)

- Zainab Zolaktaf, Fatemeh Riahi, Mahdi Shafiei, Evangelos Milios
- 2011

Community Question Answering (CQA) services contain large archives of previously asked questions and their answers. We present a statistical topic model for modeling Question-Answering archives. The model explicitly captures relationships between questions and their answers by modeling topical dependencies. We show that the model achieves improved… (More)

- Mahdi Shafiei, Katherine A Dunn, Eva Boon, Shelley M MacDonald, David A Walsh, Hong Gu +1 other
- Microbiome
- 2015

BACKGROUND
Microbiome samples often represent mixtures of communities, where each community is composed of overlapping assemblages of species. Such mixtures are complex, the number of species is huge and abundance information for many species is often sparse. Classical methods have a limited value for identifying complex features within such data.
RESULTS… (More)

- Mahdi Shafiei, Katherine A. Dunn, Hugh Chipman, Hong Gu, Joseph P. Bielawski
- PLoS Computational Biology
- 2014

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring… (More)

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