Reusable building blocks in biological systems.

One of the most widely recognized features of biological systems is their modularity. The modules that constitute biological systems are said to be redeployed and combined across several conditions, thus acting as building blocks. In this work, we analyse to what extent are these building blocks reusable as compared with those found in randomized versions of a system.

A Protocol for Generating and Exchanging (Genome-Scale) Metabolic Resource Allocation Models.

In this article, we present a protocol for generating a complete (genome-scale) metabolic resource allocation model, as well as a proposal for how to represent such models in the systems biology markup language (SBML). Such models are used to investigate enzyme levels and achievable growth rates in large-scale metabolic networks. Although the idea of metabolic resource allocation studies has been present in the field of systems biology for some years, no guidelines for generating such a model have been published up to now.

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.

Cyanobacteria are an integral part of Earth's biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium PCC 7942.

SLIMM: species level identification of microorganisms from metagenomes.

Identification and quantification of microorganisms is a significant step in studying the alpha and beta diversities within and between microbial communities respectively. Both identification and quantification of a given microbial community can be carried out using whole genome shotgun sequences with less bias than when using 16S-rDNA sequences. However, shared regions of DNA among reference genomes and taxonomic units pose a significant challenge in assigning reads correctly to their true origins.

OpenMS: a flexible open-source software platform for mass spectrometry data analysis.

High-resolution mass spectrometry (MS) has become an important tool in the life sciences, contributing to the diagnosis and understanding of human diseases, elucidating biomolecular structural information and characterizing cellular signaling networks. However, the rapid growth in the volume and complexity of MS data makes transparent, accurate and reproducible analysis difficult. We present OpenMS 2.

The steady-state assumption in oscillating and growing systems.

The steady-state assumption, which states that the production and consumption of metabolites inside the cell are balanced, is one of the key aspects that makes an efficient analysis of genome-scale metabolic networks possible. It can be motivated from two different perspectives. In the time-scales perspective, we use the fact that metabolism is much faster than other cellular processes such as gene expression.

A graph modification approach for finding core-periphery structures in protein interaction networks.

The core-periphery model for protein interaction (PPI) networks assumes that protein complexes in these networks consist of a dense core and a possibly sparse periphery that is adjacent to vertices in the core of the complex. In this work, we aim at uncovering a global core-periphery structure for a given PPI network. We propose two exact graph-theoretic formulations for this task, which aim to fit the input network to a hypothetical ground truth network by a minimum number of edge modifications.

Human CD45RA(-) FoxP3(hi) Memory-Type Regulatory T Cells Show Distinct TCR Repertoires With Conventional T Cells and Play an Important Role in Controlling Early Immune Activation.

Adoptive immunotherapy with regulatory T cells (Treg) is a new option to promote immune tolerance following solid organ transplantation (SOT). However, Treg from elderly patients awaiting transplantation are dominated by the CD45RA(-) CD62L(+) central memory type Treg subset (TregCM), and the yield of well-characterized and stable naïve Treg (TregN) is low. It is, therefore, important to determine whether these TregCM are derived from the thymus and express high stability, suppressive capacity and a broad antigen repertoire like TregN.

Generic flux coupling analysis.

Flux coupling analysis (FCA) has become a useful tool for aiding metabolic reconstructions and guiding genetic manipulations. Originally, it was introduced for constraint-based models of metabolic networks that are based on the steady-state assumption. Recently, we have shown that the steady-state assumption can be replaced by a weaker lattice-theoretic property related to the supports of metabolic fluxes.

Antilope--a Lagrangian relaxation approach to the de novo peptide sequencing problem.

Peptide sequencing from mass spectrometry data is a key step in proteome research. Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a challenge even for state-of-the-art algorithmic approaches. In this paper, we present ANTILOPE, a new fast and flexible approach based on mathematical programming.

Flux coupling analysis of metabolic networks is sensitive to missing reactions.

Genome-scale metabolic reconstructions are comprehensive, yet incomplete, models of real-world metabolic networks. While flux coupling analysis (FCA) has proved an appropriate method for analyzing metabolic relationships and for detecting functionally related reactions in such models, little is known about the impact of missing reactions on the accuracy of FCA. Based on an alternative characterization of flux coupling relations using elementary flux modes, this paper studies the changes that flux coupling relations may undergo due to missing reactions.

Statistical quality assessment and outlier detection for liquid chromatography-mass spectrometry experiments.

Background: Quality assessment methods, that are common place in engineering and industrial production, are not widely spread in large-scale proteomics experiments. But modern technologies such as Multi-Dimensional Liquid Chromatography coupled to Mass Spectrometry (LC-MS) produce large quantities of proteomic data. These data are prone to measurement errors and reproducibility problems such that an automatic quality assessment and control become increasingly important.

A consistency-based consensus algorithm for de novo and reference-guided sequence assembly of short reads.

Motivation: Novel high-throughput sequencing technologies pose new algorithmic challenges in handling massive amounts of short-read, high-coverage data. A robust and versatile consensus tool is of particular interest for such data since a sound multi-read alignment is a prerequisite for variation analyses, accurate genome assemblies and insert sequencing.

Results: A multi-read alignment algorithm for de novo or reference-guided genome assembly is presented.

LC-MSsim--a simulation software for liquid chromatography mass spectrometry data.

Background: Mass Spectrometry coupled to Liquid Chromatography (LC-MS) is commonly used to analyze the protein content of biological samples in large scale studies. The data resulting from an LC-MS experiment is huge, highly complex and noisy. Accordingly, it has sparked new developments in Bioinformatics, especially in the fields of algorithm development, statistics and software engineering.

Computational quantification of peptides from LC-MS data.

Liquid chromatography coupled to mass spectrometry (LC-MS) has become a major tool for the study of biological processes. High-throughput LC-MS experiments are frequently conducted in modern laboratories, generating an enormous amount of data per day. A manual inspection is therefore no longer a feasible task.

Segment-based multiple sequence alignment.

Motivation: Many multiple sequence alignment tools have been developed in the past, progressing either in speed or alignment accuracy. Given the importance and wide-spread use of alignment tools, progress in both categories is a contribution to the community and has driven research in the field so far.

Results: We introduce a graph-based extension to the consistency-based, progressive alignment strategy.