Dynamic interaction network inference from longitudinal microbiome data
نویسندگان
چکیده
منابع مشابه
Network Inference from Grouped Data
In medical research, economics, and the social sciences data frequently appear as subsets of a set of objects. Over the past century a number of descriptive statistics have been developed to construct network structure from such data. However, these measures lack a generating mechanism that links the inferred network structure to the observed groups. To address this issue, we propose a modelbas...
متن کاملInference in Semiparametric Dynamic Models for Binary Longitudinal Data
This article deals with the analysis of a hierarchical semiparametric model for dynamic binary longitudinal responses. The main complicating components of the model are an unknown covariate function and serial correlation in the errors. Existing estimation methods for models with these features are of O(N3), where N is the total number of observations in the sample. Therefore, nonparametric est...
متن کاملINtERAcT: Interaction Network Inference from Vector Representations of Words
In recent years, the number of biomedical publications has steadfastly grown, resulting in a rich source of untapped new knowledge. Most biomedical facts are however buried in the form of unstructured text, and their exploitation requires time-consuming manual curation of published articles. We present here INtERAcT, a novel approach to automatically extract interactions between molecular entit...
متن کاملDDGni : Dynamic delay gene - network inference from high - temporal data using gapped local alignment AQ 9
15 ABSTRACT Motivation: Inferring gene-regulatory networks is very crucial in decoding various complex mechanisms in biological systems. Synthesis of a fully functional transcriptional factor/protein from DNA involves series of reactions, leading to a delay in gene regulation. The 20 complexity increases with the dynamic delay induced by other small molecules involved in gene regulation, and no...
متن کاملDDGni: Dynamic delay gene-network inference from high-temporal data using gapped local alignment
MOTIVATION Inferring gene-regulatory networks is very crucial in decoding various complex mechanisms in biological systems. Synthesis of a fully functional transcriptional factor/protein from DNA involves series of reactions, leading to a delay in gene regulation. The complexity increases with the dynamic delay induced by other small molecules involved in gene regulation, and noisy cellular env...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Microbiome
سال: 2019
ISSN: 2049-2618
DOI: 10.1186/s40168-019-0660-3