Bioinformatics Commons^™

The International Conference On Intelligent Biology And Medicine (Icibm) 2018: Bioinformatics Towards Translational Applications, Xiaoming Liu, Lei Xie, Zhijin Wu, Kai Wang, Zhongming Zhao, Jianhuan Ruan, Degui Zhi

Publications and Research

The 2018 International Conference on Intelligent Biology and Medicine (ICIBM 2018) was held on June 10–12, 2018, in Los Angeles, California, USA. The conference consisted of a total of eleven scientific sessions, four tutorials, one poster session, four keynote talks and four eminent scholar talks, which covered a wild range of aspects of bioinformatics, medical informatics, systems biology and intelligent computing. Here, we summarize nine research articles selected for publishing in BMC Bioinformatics.

A New Insight Into Underlying Disease Mechanism Through Semi-Parametric Latent Differential Network Model, Yong He, Jiadong Ji, Lei Xie, Xinsheng Zhang, Fuzhong Xue

Publications and Research

Background

In genomic studies, to investigate how the structure of a genetic network differs between two experiment conditions is a very interesting but challenging problem, especially in high-dimensional setting. Existing literatures mostly focus on differential network modelling for continuous data. However, in real application, we may encounter discrete data or mixed data, which urges us to propose a unified differential network modelling for various data types.

Results

We propose a unified latent Gaussian copula differential network model which provides deeper understanding of the unknown mechanism than that among the observed variables. Adaptive rank-based estimation approaches are proposed with the assumption …

Predicting Serious Rare Adverse Reactions Of Novel Chemicals, Aleksandar Poleksic, Lei Xie

Publications and Research

Motivation: Adverse drug reactions (ADRs) are one of the main causes of death and a major financial burden on the world's economy. Due to the limitations of the animal model, computational prediction of serious and rare ADRs is invaluable. However, current state-of-the-art computational methods do not yield significantly better predictions of rare ADRs than random guessing.

Results: We present a novel method, based on the theory of 'compressed sensing' (CS), which can accurately predict serious side-effects of candidate and market drugs. Not only is our method able to infer new chemical-ADR associations using existing noisy, biased and incomplete databases, but …

Bpwrapper: Bioperl-Based Sequence And Tree Utilities For Rapid Prototyping Of Bioinformatics Pipelines, Yözen Hernández, Rocky Bernstein, Pedro Pagan, Levy Vargas, William Mccaig, Girish Ramrattan, Saymon Akther, Amanda Larracuente, Lia Di, Filipe G. Vieira, Weigang Qiu

Publications and Research

Abstract:

Background: Automated bioinformatics workflows are more robust, easier to maintain, and results more reproducible when built with command-line utilities than with custom-coded scripts. Command-line utilities further benefit by relieving bioinformatics developers to learn the use of, or to interact directly with, biological software libraries. There is however a lack of command-line utilities that leverage popular Open Source biological software toolkits such as BioPerl (http://bioperl.org) to make many of the well-designed, robust, and routinely used biological classes available for a wider base of end users.

Results: Designed as standard utilities for UNIX-family operating systems, BpWrapper makes functionality of some of …