Andreas Hildebrandt

OpenMS – An open-source software framework for mass spectrometry

BackgroundMass spectrometry is an essential analytical technique for high-throughput analysis in proteomics and metabolomics. The development of new separation techniques, precise mass analyzers and experimental protocols is a very active field of research. This leads to more complex experimental setups yielding ever increasing amounts of data. Consequently, analysis of the data is currently often the bottleneck for experimental studies. Although software tools for many data analysis tasks are available today, they are often hard to combine with each other or not flexible enough to allow for rapid prototyping of a new analysis workflow.ResultsWe present OpenMS, a software framework for rapid application development in mass spectrometry. OpenMS has been designed to be portable, easy-to-use and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis. This has already been demonstrated in several studies.ConclusionOpenMS is available under the Lesser GNU Public License (LGPL) from the project website at http://www.openms.de.

High-accuracy peak picking of proteomics data using wavelet techniques.

A new peak picking algorithm for the analysis of mass spectrometric (MS) data is presented. It is independent of the underlying machine or ionization method, and is able to resolve highly convoluted and asymmetric signals. The method uses the multiscale nature of spectrometric data by first detecting the mass peaks in the wavelet-transformed signal before a given asymmetric peak function is fitted to the raw data. In an optional third stage, the resulting fit can be further improved using techniques from nonlinear optimization. In contrast to currently established techniques (e.g. SNAP, Apex) our algorithm is able to separate overlapping peaks of multiply charged peptides in ESI-MS data of low resolution. Its improved accuracy with respect to peak positions makes it a valuable preprocessing method for MS-based identification and quantification experiments. The method has been validated on a number of different annotated test cases, where it compares favorably in both runtime and accuracy with currently established techniques. An implementation of the algorithm is freely available in our open source framework OpenMS.

The reverse transcription signature of N-1-methyladenosine in RNA-Seq is sequence dependent

The combination of Reverse Transcription (RT) and high-throughput sequencing has emerged as a powerful combination to detect modified nucleotides in RNA via analysis of either abortive RT-products or of the incorporation of mismatched dNTPs into cDNA. Here we simultaneously analyze both parameters in detail with respect to the occurrence of N-1-methyladenosine (m1A) in the template RNA. This naturally occurring modification is associated with structural effects, but it is also known as a mediator of antibiotic resistance in ribosomal RNA. In structural probing experiments with dimethylsulfate, m1A is routinely detected by RT-arrest. A specifically developed RNA-Seq protocol was tailored to the simultaneous analysis of RT-arrest and misincorporation patterns. By application to a variety of native and synthetic RNA preparations, we found a characteristic signature of m1A, which, in addition to an arrest rate, features misincorporation as a significant component. Detailed analysis suggests that the signature depends on RNA structure and on the nature of the nucleotide 3′ of m1A in the template RNA, meaning it is sequence dependent. The RT-signature of m1A was used for inspection and confirmation of suspected modification sites and resulted in the identification of hitherto unknown m1A residues in trypanosomal tRNA.

Universality of protein reentrant condensation in solution induced by multivalent metal ions

The effective interactions and phase behavior of protein solutions under strong electrostatic coupling conditions are difficult to understand due to the complex charge pattern and irregular geometry of protein surfaces. This distinguishes them from related systems such as DNA or conventional colloids. In this work, we discuss the question of universality of the reentrant condensation (RC) of proteins in solution induced by multivalent counterions, i.e., redissolution on adding further salts after phase separation, as recently discovered (Zhang et al., Phys Rev Lett 2008; 101:148101). The discussion is based on a systematic investigation of five different proteins with different charge patterns and five different multivalent counterions. Zeta potential measurements confirm the effective charge inversion of proteins in the reentrant regime via binding of multivalent counterions, which is supported by Monte Carlo simulations. Charge inversion by trivalent cations requires an overall negative net charge of the protein. Statistical analysis of a representative set of protein sequences reveals that, in theory, this effect could be possible for about half of all proteins. Our results can be exploited for the control of the phase behavior of proteins, in particular facilitating protein crystallization. Proteins 2010.

BALL - biochemical algorithms library 1.3

BackgroundThe Biochemical Algorithms Library (BALL) is a comprehensive rapid application development framework for structural bioinformatics. It provides an extensive C++ class library of data structures and algorithms for molecular modeling and structural bioinformatics. Using BALL as a programming toolbox does not only allow to greatly reduce application development times but also helps in ensuring stability and correctness by avoiding the error-prone reimplementation of complex algorithms and replacing them with calls into the library that has been well-tested by a large number of developers. In the ten years since its original publication, BALL has seen a substantial increase in functionality and numerous other improvements.ResultsHere, we discuss BALLs current functionality and highlight the key additions and improvements: support for additional file formats, molecular edit-functionality, new molecular mechanics force fields, novel energy minimization techniques, docking algorithms, and support for cheminformatics.ConclusionsBALL is available for all major operating systems, including Linux, Windows, and MacOS X. It is available free of charge under the Lesser GNU Public License (LPGL). Parts of the code are distributed under the GNU Public License (GPL). BALL is available as source code and binary packages from the project web site at http://www.ball-project.org. Recently, it has been accepted into the debian project; integration into further distributions is currently pursued.

BALLView: a tool for research and education in molecular modeling

We present BALLView, a molecular viewer and modeling tool. It combines state-of-the-art visualization capabilities with powerful modeling functionality including implementations of force field methods and continuum electrostatics models. BALLView is a versatile and extensible tool for research in structural bioinformatics and molecular modeling. Furthermore, the convenient and intuitive graphical user interface offers novice users direct access to the full functionality, rendering it ideal for teaching. Through an interface to the object-oriented scripting language Python it is easily extensible.

A dynamic program analysis to find floating-point accuracy problems

Programs using floating-point arithmetic are prone to accuracy problems caused by rounding and catastrophic cancellation. These phenomena provoke bugs that are notoriously hard to track down: the program does not necessarily crash and the results are not necessarily obviously wrong, but often subtly inaccurate. Further use of these values can lead to catastrophic errors. In this paper, we present a dynamic program analysis that supports the programmer in finding accuracy problems. Our analysis uses binary translation to perform every floating-point computation side by side in higher precision. Furthermore, we use a lightweight slicing approach to track the evolution of errors. We evaluate our analysis by demonstrating that it catches wellknown floating-point accuracy problems and by analyzing the Spec CFP2006 floating-point benchmark. In the latter, we show how our tool tracks down a catastrophic cancellation that causes a complete loss of accuracy leading to a meaningless program result. Finally, we apply our program to a complex, real-world bioinformatics application in which our program detected a serious cancellation. Correcting the instability led not only to improved quality of the result, but also to an improvement of the programs run time.In this paper, we present a dynamic program analysis that supports the programmer in finding accuracy problems. Our analysis uses binary translation to perform every floating-point computation side by side in higher precision. Furthermore, we use a lightweight slicing approach to track the evolution of errors. We evaluate our analysis by demonstrating that it catches wellknown floating-point accuracy problems and by analyzing the SpecfiCFP2006 floating-point benchmark. In the latter, we show how our tool tracks down a catastrophic cancellation that causes a complete loss of accuracy leading to a meaningless program result. Finally, we apply our program to a complex, real-world bioinformatics application in which our program detected a serious cancellation. Correcting the instability led not only to improved quality of the result, but also to an improvement of the programs run time.

Novel formulation of nonlocal electrostatics

The accurate modeling of the dielectric properties of water is crucial for many applications in physics, computational chemistry, and molecular biology. This becomes possible in the framework of nonlocal electrostatics, for which we propose a novel formulation allowing for numerical solutions for the nontrivial molecular geometries arising in the applications mentioned before. Our approach is based on the introduction of a secondary field psi, which acts as the potential for the rotation free part of the dielectric displacement field D. For many relevant models, the dielectric function of the medium can be expressed as the Greens function of a local differential operator. In this case, the resulting coupled Poisson (-Boltzmann) equations for psi and the electrostatic potential phi reduce to a system of coupled partial differential equations. The approach is illustrated by its application to simple geometries.

BALLView: an object-oriented molecular visualization and modeling framework.

SummaryWe present BALLView, an extensible tool for visualizing and modeling bio-molecular structures. It provides a variety of different models for bio-molecular visualization, e.g. ball-and-stick models, molecular surfaces, or ribbon models. In contrast to most existing visualization tools, BALLView also offers rich functionality for molecular modeling and simulation, including molecular mechanics methods (AMBER and CHARMM force fields), continuum electrostatics methods employing a Finite-Difference Poisson Boltzmann solver, and secondary structure calculation. Results of these computations can be exported as publication quality images or as movies. Even unexperienced users have direct access to this functionality through an intuitive graphical user interface, which makes BALLView particularly useful for teaching. For more advanced users, BALLView is extensible in different ways. Owing to its framework design, extension on the level of C‰+‰‰+ code is very convenient. In addition, an interface to the scripting language Python allows the interactive rapid prototyping of new methods. BALLView is portable and runs on all major platforms (Windows, MacOS X, Linux, most Unix flavors). It is available free of charge under the GNU Public License (GPL) from our website http://www.ballview.org.

Highly accelerated feature detection in proteomics data sets using modern graphics processing units

MOTIVATION Mass spectrometry (MS) is one of the most important techniques for high-throughput analysis in proteomics research. Due to the large number of different proteins and their post-translationally modified variants, the amount of data generated by a single wet-lab MS experiment can easily exceed several gigabytes. Hence, the time necessary to analyze and interpret the measured data is often significantly larger than the time spent on sample preparation and the wet-lab experiment itself. Since the automated analysis of this data is hampered by noise and baseline artifacts, more sophisticated computational techniques are required to handle the recorded mass spectra. Obviously, there is a clear tradeoff between performance and quality of the analysis, which is currently one of the most challenging problems in computational proteomics. RESULTS Using modern graphics processing units (GPUs), we implemented a feature finding algorithm based on a hand-tailored adaptive wavelet transform that drastically reduces the computation time. A further speedup can be achieved exploiting the multi-core architecture of current computing devices, which leads to up to an approximately 200-fold speed-up in our computational experiments. In addition, we will demonstrate that several approximations necessary on the CPU to keep run times bearable, become obsolete on the GPU, yielding not only faster, but also improved results. AVAILABILITY An open source implementation of the CUDA-based algorithm is available via the software framework OpenMS (http://www.openms.de). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.