Matthias E. Futschik

Bio: Matthias E. Futschik is an academic researcher from University of the Algarve. The author has contributed to research in topics: Human interactome & Gene expression profiling. The author has an hindex of 33, co-authored 84 publications receiving 3831 citations. Previous affiliations of Matthias E. Futschik include Charité & Humboldt University of Berlin.

Mfuzz: a software package for soft clustering of microarray data.

Abstract: For the analysis of microarray data, clustering techniques are frequently used. Most of such methods are based on hard clustering of data wherein one gene (or sample) is assigned to exactly one cluster. Hard clustering, however, suffers from several drawbacks such as sensitivity to noise and information loss. In contrast, soft clustering methods can assign a gene to several clusters. They can overcome shortcomings of conventional hard clustering techniques and offer further advantages. Thus, we constructed an R package termed Mfuzz implementing soft clustering tools for microarray data analysis. The additional package Mfuzzgui provides a convenient TclTk based graphical user interface. Availability The R package Mfuzz and Mfuzzgui are available at http://itb1.biologie.hu-berlin.de/~futschik/software/R/Mfuzz/index.html. Their distribution is subject to GPL version 2 license.

Tight regulation of unstructured proteins: from transcript synthesis to protein degradation.

Abstract: Altered abundance of several intrinsically unstructured proteins (IUPs) has been associated with perturbed cellular signaling that may lead to pathological conditions such as cancer. Therefore, it is important to understand how cells precisely regulate the availability of IUPs. We observed that regulation of transcript clearance, proteolytic degradation, and translational rate contribute to controlling the abundance of IUPs, some of which are present in low amounts and for short periods of time. Abundant phosphorylation and low stochasticity in transcription and translation indicate that the availability of IUPs can be finely tuned. Fidelity in signaling may require that most IUPs be available in appropriate amounts and not present longer than needed.

Noise-robust soft clustering of gene expression time-course data

Abstract: Clustering is an important tool in microarray data analysis. This unsupervised learning technique is commonly used to reveal structures hidden in large gene expression data sets. The vast majority of clustering algorithms applied so far produce hard partitions of the data, i.e. each gene is assigned exactly to one cluster. Hard clustering is favourable if clusters are well separated. However, this is generally not the case for microarray time-course data, where gene clusters frequently overlap. Additionally, hard clustering algorithms are often highly sensitive to noise. To overcome the limitations of hard clustering, we applied soft clustering which offers several advantages for researchers. First, it generates accessible internal cluster structures, i.e. it indicates how well corresponding clusters represent genes. This can be used for the more targeted search for regulatory elements. Second, the overall relation between clusters, and thus a global clustering structure, can be defined. Additionally, soft clustering is more noise robust and a priori pre-filtering of genes can be avoided. This prevents the exclusion of biologically relevant genes from the data analysis. Soft clustering was implemented here using the fuzzy c-means algorithm. Procedures to find optimal clustering parameters were developed. A software package for soft clustering has been developed based on the open-source statistical language R. The package called Mfuzz is freely available.

Genome-wide expression dynamics of a marine virus and host reveal features of co-evolution

Abstract: It's known that interactions between bacteria and their viruses (or phages) can result in a degree of co-evolution of host and phage. A picture of just how close that relationship can become is given by whole-genome expression profiling of the marine cyanobacterium Prochlorococcus and its T7-like cyanophage during infection. A number of host genes are expressed in a coordinated fashion during phage infection, and the phage seem to have evolved to make good use of the gene products. These cyanobacteria are ubiquitous in the oceans and dominant in their particular niche. It seems likely that evolutionary cooperation between host and phage contributes to the success of both partners. Phages have a major impact on the evolution of their bacterial hosts. Providing the first whole genome expression profiling of the marine cyanobacterium Prochlorococcus and its T7-like cyanophage during lytic infection reveals potential mechanistic features of this co-evolutionary process. Interactions between bacterial hosts and their viruses (phages) lead to reciprocal genome evolution through a dynamic co-evolutionary process1,2,3,4,5. Phage-mediated transfer of host genes—often located in genome islands—has had a major impact on microbial evolution1,4,6. Furthermore, phage genomes have clearly been shaped by the acquisition of genes from their hosts2,3,5. Here we investigate whole-genome expression of a host and phage, the marine cyanobacterium Prochlorococcus MED4 and the T7-like cyanophage P-SSP7, during lytic infection, to gain insight into these co-evolutionary processes. Although most of the phage genome was linearly transcribed over the course of infection, four phage-encoded bacterial metabolism genes formed part of the same expression cluster, even though they are physically separated on the genome. These genes—encoding photosystem II D1 (psbA), high-light inducible protein (hli), transaldolase (talC) and ribonucleotide reductase (nrd)—are transcribed together with phage DNA replication genes and seem to make up a functional unit involved in energy and deoxynucleotide production for phage replication in resource-poor oceans. Also unique to this system was the upregulation of numerous genes in the host during infection. These may be host stress response genes and/or genes induced by the phage. Many of these host genes are located in genome islands and have homologues in cyanophage genomes. We hypothesize that phage have evolved to use upregulated host genes, leading to their stable incorporation into phage genomes and their subsequent transfer back to hosts in genome islands. Thus activation of host genes during infection may be directing the co-evolution of gene content in both host and phage genomes.

Choreography of the transcriptome, photophysiology, and cell cycle of a minimal photoautotroph, prochlorococcus.

Abstract: The marine cyanobacterium Prochlorococcus MED4 has the smallest genome and cell size of all known photosynthetic organisms. Like all phototrophs at temperate latitudes, it experiences predictable daily variation in available light energy which leads to temporal regulation and partitioning of key cellular processes. To better understand the tempo and choreography of this minimal phototroph, we studied the entire transcriptome of the cell over a simulated daily light-dark cycle, and placed it in the context of diagnostic physiological and cell cycle parameters. All cells in the culture progressed through their cell cycles in synchrony, thus ensuring that our measurements reflected the behavior of individual cells. Ninety percent of the annotated genes were expressed, and 80% had cyclic expression over the diel cycle. For most genes, expression peaked near sunrise or sunset, although more subtle phasing of gene expression was also evident. Periodicities of the transcripts of genes involved in physiological processes such as in cell cycle progression, photosynthesis, and phosphorus metabolism tracked the timing of these activities relative to the light-dark cycle. Furthermore, the transitions between photosynthesis during the day and catabolic consumption of energy reserves at night— metabolic processes that share some of the same enzymes — appear to be tightly choreographed at the level of RNA expression. In-depth investigation of these patterns identified potential regulatory proteins involved in balancing these opposing pathways. Finally, while this analysis has not helped resolve how a cell with so little regulatory capacity, and a ‘deficient’ circadian mechanism, aligns its cell cycle and metabolism so tightly to a light-dark cycle, it does provide us with a valuable framework upon which to build when the Prochlorococcus proteome and metabolome become available.

clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters

Abstract: Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters The analysis module and visualization module were combined into a reusable workflow Currently, clusterProfiler supports three species, including humans, mice, and yeast Methods provided in this package can be easily extended to other species and ontologies The clusterProfiler package is released under Artistic-20 License within Bioconductor project The source code and vignette are freely available at http://bioconductororg/packages/release/bioc/html/clusterProfilerhtml

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Human Protein Reference Database—2009 update

Abstract: Human Protein Reference Database (HPRD--http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system--Human Proteinpedia (http://www.humanproteinpedia.org/)--through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15,000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.