Fast metabolite identification with Input Output Kernel Regression.

Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach.

Analysis of differential splicing suggests different modes of short-term splicing regulation.

Motivation: Alternative splicing is an important mechanism in which the regions of pre-mRNAs are differentially joined in order to form different transcript isoforms. Alternative splicing is involved in the regulation of normal physiological functions but also linked to the development of diseases such as cancer. We analyse differential expression and splicing using RNA-sequencing time series in three different settings: overall gene expression levels, absolute transcript expression levels and relative transcript expression levels.

An ecometric analysis of the fossil mammal record of the Turkana Basin.

Although ecometric methods have been used to analyse fossil mammal faunas and environments of Eurasia and North America, such methods have not yet been applied to the rich fossil mammal record of eastern Africa. Here we report results from analysis of a combined dataset spanning east and west Turkana from Kenya between 7 and 1 million years ago (Ma). We provide temporally and spatially resolved estimates of temperature and precipitation and discuss their relationship to patterns of faunal change, and propose a new hypothesis to explain the lack of a temperature trend.

On the Identifiability of Transmission Dynamic Models for Infectious Diseases.

Understanding the transmission dynamics of infectious diseases is important for both biological research and public health applications. It has been widely demonstrated that statistical modeling provides a firm basis for inferring relevant epidemiological quantities from incidence and molecular data. However, the complexity of transmission dynamic models presents two challenges: (1) the likelihood function of the models is generally not computable, and computationally intensive simulation-based inference methods need to be employed, and (2) the model may not be fully identifiable from the available data.

Gaussian process test for high-throughput sequencing time series: application to experimental evolution.

Motivation: Recent advances in high-throughput sequencing (HTS) have made it possible to monitor genomes in great detail. New experiments not only use HTS to measure genomic features at one time point but also monitor them changing over time with the aim of identifying significant changes in their abundance. In population genetics, for example, allele frequencies are monitored over time to detect significant frequency changes that indicate selection pressures.

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations.

Motivation: Data analysis for metabolomics suffers from uncertainty because of the noisy measurement technology and the small sample size of experiments. Noise and the small sample size lead to a high probability of false findings. Further, individual compounds have natural variation between samples, which in many cases renders them unreliable as biomarkers.

Exploration and retrieval of whole-metagenome sequencing samples.

Motivation: Over the recent years, the field of whole-metagenome shotgun sequencing has witnessed significant growth owing to the high-throughput sequencing technologies that allow sequencing genomic samples cheaper, faster and with better coverage than before. This technical advancement has initiated the trend of sequencing multiple samples in different conditions or environments to explore the similarities and dissimilarities of the microbial communities. Examples include the human microbiome project and various studies of the human intestinal tract.