Insights into Phosphate Cooperativity and Influence of Substrate Modifications on Binding and Catalysis of Hexameric Purine Nucleoside Phosphorylases

The hexameric purine nucleoside phosphorylase from Bacillus subtilis (BsPNP233) displays great potential to produce nucleoside analogues in industry and can be exploited in the development of new anti-tumor gene therapies. In order to provide structural basis for enzyme and substrates rational optimization, aiming at those applications, the present work shows a thorough and detailed structural description of the binding mode of substrates and nucleoside analogues to the active site of the hexameric BsPNP233. Here we report the crystal structure of BsPNP233 in the apo form and in complex with 11 ligands, including clinically relevant compounds. The crystal structure of six ligands (adenine, 2'deoxyguanosine, aciclovir, ganciclovir, 8-bromoguanosine, 6-chloroguanosine) in complex with a hexameric PNP are presented for the first time. Our data showed that free bases adopt alternative conformations in the BsPNP233 active site and indicated that binding of the co-substrate (2'deoxy) ribose 1-phosphate might contribute for stabilizing the bases in a favorable orientation for catalysis. The BsPNP233-adenosine complex revealed that a hydrogen bond between the 5' hydroxyl group of adenosine and Arg(43*) side chain contributes for the ribosyl radical to adopt an unusual C3'-endo conformation. The structures with 6-chloroguanosine and 8-bromoguanosine pointed out that the Cl-6 and Br-8 substrate modifications seem to be detrimental for catalysis and can be explored in the design of inhibitors for hexameric PNPs from pathogens. Our data also corroborated the competitive inhibition mechanism of hexameric PNPs by tubercidin and suggested that the acyclic nucleoside ganciclovir is a better inhibitor for hexameric PNPs than aciclovir. Furthermore, comparative structural analyses indicated that the replacement of Ser(90) by a threonine in the B. cereus hexameric adenosine phosphorylase (Thr(91)) is responsible for the lack of negative cooperativity of phosphate binding in this enzyme.

A Simple Method to Evaluate, Correlate and Predict Boiling and Flash Points of Alkynes

Boiling points (T-B) of acyclic alkynes are predicted from their boiling point numbers (Y-BP) with the relationship T-B(K) = -16.802Y(BP)(2/3) + 337.377Y(BP)(1/3) - 437.883. In turn, Y-BP values are calculated from structure using the equation Y-BP = 1.726 + A(i) + 2.779C + 1.716M(3) + 1.564M + 4.204E(3) + 3.905E + 5.007P - 0.329D + 0.241G + 0.479V + 0.967T + 0.574S. Here A(i) depends on the substitution pattern of the alkyne and the remainder of the equation is the same as that reported earlier for alkanes. For a data set consisting of 76 acyclic alkynes, the correlation of predicted and literature T-B values had an average absolute deviation of 1.46 K, and the R-2 of the correlation was 0.999. In addition, the calculated Y-BP values can be used to predict the flash points of alkynes.

Exploring the intrinsic polar [4?+?2+] cycloaddition reactivity of gaseous carbosulfonium and carboxonium ions

Gas-phase reactions of model carbosulfonium ions (CH3-S+?=?CH2; CH3CH2-S+?=?CH2 and Ph-S+?=?CH2) and an O-analogue carboxonium ion (CH3-O+?=?CH2) with acyclic (isoprene, 1,3-butadiene, methyl vinyl ketone) and cyclic (1,3-cyclohexadiene, thiophene, furan) conjugated dienes were systematically investigated by pentaquadrupole mass spectrometry. As corroborated by B3LYP/6-311?G(d,p) calculations, the carbosulfonium ions first react at large extents with the dienes forming adducts via simple addition. The nascent adducts, depending on their stability and internal energy, react further via two competitive channels: (1) in reactions with acyclic dienes via cyclization that yields formally [4?+?2+] cycloadducts, or (2) in reactions with the cyclic dienes via dissociation by HSR loss that yields methylenation (net CH+ transfer) products. In great contrast to its S-analogues, CH3-O+?=?CH2 (as well as C2H5-O+?=?CH2 and Ph-O+?=?CH2 in reactions with isoprene) forms little or no adduct and proton transfer is the dominant reaction channel. Isomerization to more acidic protonated aldehydes in the course of reaction seems to be the most plausible cause of the contrasting reactivity of carboxonium ions. The CH2?=?CH-O+?=?CH2 ion forms an abundant [4?+?2+] cycloadduct with isoprene, but similar to the behavior of such alpha,beta-unsaturated carboxonium ions in solution, seems to occur across the C?=?C bond. Copyright (c) 2012 John Wiley & Sons, Ltd.

A simple method to evaluate, correlate and predict boiling and flash points of alkynes

Boiling points (T B) of acyclic alkynes are predicted from their boiling point numbers (Y BP) with the relationship T B(K) = -16.802Y BP2/3 + 337.377Y BP1/3 - 437.883. In turn, Y BP values are calculated from structure using the equation Y BP = 1.726 + Ai + 2.779C + 1.716M3 + 1.564M + 4.204E3 + 3.905E + 5.007P - 0.329D + 0.241G + 0.479V + 0.967T + 0.574S. Here Ai depends on the substitution pattern of the alkyne and the remainder of the equation is the same as that reported earlier for alkanes. For a data set consisting of 76 acyclic alkynes, the correlation of predicted and literature T B values had an average absolute deviation of 1.46 K, and the R² of the correlation was 0.999. In addition, the calculated Y BP values can be used to predict the flash points of alkynes.

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

Die Synthese von Glycopeptiden und Glycopeptid-Protein-Konjugaten mit einer Partialstruktur des tumorassoziierten Mucins MUC1 zur Entwicklung von Tumorvakzinen

„Synthese von Glycopeptiden und Glycopeptid-Protein-Konjugaten mit einer Partialstruktur des tumorassoziierten Mucins MUC1 zur Entwicklung von Tumorvakzinen“ Das Glycoprotein MUC1 ist in Tumorepithelzellen sonderlich stark überexprimiert und wegen der vorzeitig einsetzenden Sialylierung sind die Saccharid-Epitope der O-Glycanketten stark verkürzt (sog. tumorassoziierte Antigene). Dadurch werden auch bisher verborgene Peptidepitope des Glycoprotein-Rückgrates auf der Zelloberfläche der Epithelzellen zugänglich, die als fremd von den Zellen des Immunsystems erkannt werden können. Dies macht das MUC1-Zelloberfächenmolekül zu einem Zielmolekül in der Entwicklung von Tumorvakzinen. Diese beiden strukturellen Besonderheiten wurden in der Synthese von Glycohexadecapeptiden verbunden, indem die veränderten tumorassoziierten Saccharidstrukturen TN-, STN- und T-Antigen als Glycosylaminosäure-Festphasenbausteine synthetisiert wurden und in das Peptidepitop der Wiederholungseinheit des MUC1 durch Glycopeptid-Festphasensynthese eingebaut wurden. Wegen der inhärenten schwachen Immunogenität der kurzen Glycopeptide müssen die synthetisierten Glycopeptidstrukturen an ein Trägerprotein, welches das Immunsystem stimuliert, gebunden werden. Zur Anbindung der Glycopeptide ist ein selektives Kupplungsverfahren nötig, um definierte und strukturell einheitliche Glycopeptid-Protein-Konjugate zu erhalten. Es konnte eine neue Methode entwickelt werden, bei der die Konjugation durch eine radikalische Additionsreaktion von als Allylamide funktionalisierten Glycopeptiden an ein Thiol-modifiziertes Trägerprotein erfolgte. Dazu wurde anhand von synthetisierten, als Allylamide modifizierten Modellaminosäuren untersucht, ob diese Reaktion generell für eine Biokonjugation geeignet ist und etwaige Nebenreaktionen auftreten können. Mit dieser Methode konnten verschiedene MUC1-Glycopeptid-Trägerprotein-Konjugate hergestellt werden, deren immunologische Untersuchung noch bevorsteht. Das tumorassoziierte MUC1 nimmt in der immundominanten Region seiner Wiederholungseinheit eine knaufartige Struktur ein. Für die Entwicklung von selektiven Tumorvakzinen ist es von großer Bedeutung möglichst genau die Struktur der veränderten Zelloberflächenmoleküle nachzubilden. Durch die Synthese von cyclischen (Glyco)Peptiden wurde dieses Strukturelement fixiert. Dazu wurden olefinische Aminosäure Festphasenbausteine hergestellt, die zusammen mit den oben genannten Glycosylaminosäuren mittels einer Glycopeptid-Festphasensynthese in acyclische Glycopeptide eingebaut wurden. Diese wurden dann durch Ringschlussmetathese zyklisiert und im Anschluss reduziert und vollständig deblockiert. In einem dritten Projekt wurde der Syntheseweg zur Herstellung einer C-Glycosylaminosäure mit einer N-Acetylgalactosamin-Einheit entwickelt. Wichtige Schritte bei der von Glucosamin ausgehenden Synthese sind die Keck-Allylierung, eine Epimerisierung, die Herstellung eines Brom-Dehydroalanin-Derivates und eine B-Alkyl-Suzuki-Miyaura-Kreuzkupplung sowie Schutzgruppenoperationen. Der racemische Baustein konnte dann in der Peptid-Festphasensynthese eines komplexen MUC1-Tetanustoxin-Konjugates eingesetzt werden.

Über das Vermessen tubulärer Strukturen in der Computertomographie

Die chronisch obstruktive Lungenerkrankung (engl. chronic obstructive pulmonary disease, COPD) ist ein Überbegriff für Erkrankungen, die zu Husten, Auswurf und Dyspnoe (Atemnot) in Ruhe oder Belastung führen - zu diesen werden die chronische Bronchitis und das Lungenemphysem gezählt. Das Fortschreiten der COPD ist eng verknüpft mit der Zunahme des Volumens der Wände kleiner Luftwege (Bronchien). Die hochauflösende Computertomographie (CT) gilt bei der Untersuchung der Morphologie der Lunge als Goldstandard (beste und zuverlässigste Methode in der Diagnostik). Möchte man Bronchien, eine in Annäherung tubuläre Struktur, in CT-Bildern vermessen, so stellt die geringe Größe der Bronchien im Vergleich zum Auflösungsvermögen eines klinischen Computertomographen ein großes Problem dar. In dieser Arbeit wird gezeigt wie aus konventionellen Röntgenaufnahmen CT-Bilder berechnet werden, wo die mathematischen und physikalischen Fehlerquellen im Bildentstehungsprozess liegen und wie man ein CT-System mittels Interpretation als lineares verschiebungsinvariantes System (engl. linear shift invariant systems, LSI System) mathematisch greifbar macht. Basierend auf der linearen Systemtheorie werden Möglichkeiten zur Beschreibung des Auflösungsvermögens bildgebender Verfahren hergeleitet. Es wird gezeigt wie man den Tracheobronchialbaum aus einem CT-Datensatz stabil segmentiert und mittels eines topologieerhaltenden 3-dimensionalen Skelettierungsalgorithmus in eine Skelettdarstellung und anschließend in einen kreisfreien Graphen überführt. Basierend auf der linearen System Theorie wird eine neue, vielversprechende, integral-basierte Methodik (IBM) zum Vermessen kleiner Strukturen in CT-Bildern vorgestellt. Zum Validieren der IBM-Resultate wurden verschiedene Messungen an einem Phantom, bestehend aus 10 unterschiedlichen Silikon Schläuchen, durchgeführt. Mit Hilfe der Skelett- und Graphendarstellung ist ein Vermessen des kompletten segmentierten Tracheobronchialbaums im 3-dimensionalen Raum möglich. Für 8 zweifach gescannte Schweine konnte eine gute Reproduzierbarkeit der IBM-Resultate nachgewiesen werden. In einer weiteren, mit IBM durchgeführten Studie konnte gezeigt werden, dass die durchschnittliche prozentuale Bronchialwandstärke in CT-Datensätzen von 16 Rauchern signifikant höher ist, als in Datensätzen von 15 Nichtrauchern. IBM läßt sich möglicherweise auch für Wanddickenbestimmungen bei Problemstellungen aus anderen Arbeitsgebieten benutzen - kann zumindest als Ideengeber dienen. Ein Artikel mit der Beschreibung der entwickelten Methodik und der damit erzielten Studienergebnisse wurde zur Publikation im Journal IEEE Transactions on Medical Imaging angenommen.

Novel Synthetic Procedures in Organocatalysis

The main aim of my PhD project was the design and the synthesis of new pyrrolidine organocatalysts. New effective ferrocenyl pyrrolidine catalysts, active in benchmark organocatalytic reactions, has been developed. The ferrocenyl moiety, in combination with simple ethyl chains, is capable of fixing the enamine conformation addressing the approach trajectory of the nucleophile in the reaction. The results obtained represent an interesting proof-of-concept, showing for the first time the remarkable effectiveness of the ferrocenyl moiety in providing enantioselectivity through conformational selection. This approach could be viably employed in the rational design of ligands for metal or organocatalysts. Other hindered secondary amines has been prepared from alkylation of acyclic chiral nitroderivatives with alcohols in a highly diastereoselective fashion, giving access to functionalized, useful organocatalytic chiral pyrrolidines. A family of new pyrrolidines bearing sterogenic centers and functional groups can be readily accessible by this methodology. The second purpose of the project was to study in deep the reactivity of stabilized carbocations in new metal-free and organocatalytic reactions. By taking advantage of the results from the kinetic studies described by Mayr, a simple and effective procedure for the direct formylation of aryltetrafluoroborate salts, has been development. The coupling of a range of aryl- and heteroaryl- trifluoroborate salts with 1,3-benzodithiolylium tetrafluoroborate, has been attempted in moderate to good yields. Finally, a simple and general methodology for the enamine-mediated enantioselective α-alkylation of α-substituted aldehydes with 1,3-benzodithiolylium tetrafluoroborate has been reported. The introduction of the benzodithiole moiety permit the installation of different functional groups due to its chameleonic behaviour.

Au(I) Catalyzed Manipulation of Propargylic Alcohols: A New Route Towards the Synthesis of Indole Alkaloids

In this work we presented several aspects regarding the possibility to use readily available propargylic alcohols as acyclic precursors to develop new stereoselective [Au(I)]-catalyzed cascade reactions for the synthesis of highly complex indole architectures. The use of indole-based propargylic alcohols of type 1 in a stereoselective [Au(I)]-catalyzed hydroindolynation/immiun trapping reactive sequence opened access to a new class of tetracyclic indolines, dihydropyranylindolines A and furoindolines B. An enantioselective protocol was futher explored in order to synthesize this molecules with high yields and ee. The suitability of propargylic alcohols in [Au(I)]-catalyzed cascade reactions was deeply investigated by developing cascade reactions in which was possible not only to synthesize the indole core but also to achieve a second functionalization. Aniline based propargylic alcohols 2 were found to be modular acyclic precursors for the synthesis of [1,2-a] azepinoindoles C. In describing this reactivity we additionally reported experimental evidences for an unprecedented NHCAu(I)-vinyl specie which in a chemoselective fashion, led to the annulation step, synthesizing the N1-C2-connected seven membered ring. The chemical flexibility of propargylic alcohols was further explored by changing the nature of the chemical surrounding with different preinstalled N-alkyl moiety in propargylic alcohols of type 3. Particularly, in the case of a primary alcohol, [Au(I)] catalysis was found to be prominent in the synthesis of a new class of [4,3-a]-oxazinoindoles D while the use of an allylic alcohol led to the first example of [Au(I)] catalyzed synthesis and enantioselective functionalization of this class of molecules (D*). With this work we established propargylic alcohols as excellent acyclic precursor to developed new [Au(I)]-catalyzed cascade reaction and providing new catalytic synthetic tools for the stereoselective synthesis of complex indole/indoline architectures.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Nicht-wässrige Emulsionen zur Erzeugung neuer Nanopartikel

In der eingereichten Arbeit wurde die Nutzung von nicht-wässrigen Emulsionen, bestehend aus zwei organischen, aprotischen Lösungsmitteln, zur Erzeugung verschiedener polymerer Nanopartikel beschrieben. Diese Zweiphasenmischungen und die Verwendung maßgeschneiderter Emulgatoren bestehend aus Poly(isopren-block-methylmethacrylat) ermöglichten den Zugang zu einer Vielzahl an Reaktionen und Prozessen, welche in wässrigen Emulsionen bisher nicht oder nur schwer möglich waren. Die Generierung von Partikeln auf Basis katalytischer Polymerisationen erfolgte unter Verwendung der Ringöffnenden Metathese-Polymerisation (ROMP), der Acyclischen Dien-Metathese-Polymerisation (ADMET), der Cyclopolymerisation von α,ω-Diinen und der Ni-katalysierten Polymerisation von Isocyaniden. Mittels ROMP konnten stabile Dispersionen erzeugt werden, welche Partikel mit verschiedensten Molekulargewichten, Größen und Morphologien enthielten. Diese Eigenschaften konnten durch die Wahl des Monomers, die Katalysatorkonzentration oder den Emulgatortyp beeinflusst werden. Des Weiteren wurden Partikel mit komplexen Morphologien wie Kern-Schale-Strukturen synthetisiert. Dazu erfolgte die Generierung von Partikeln aus Poly(urethan) oder Poly(norbornenderivaten), welche in situ und ohne intermediäre Aufarbeitung mit einer Schale aus Poly(methacrylat) versehen wurden. Der Nachweis dieser Strukturen gelang mittels verschiedener Schwermetall-Markierungsverfahren in der Transmissionselektronenmikroskopie. Schlussendlich erfolgte die Herstellung von hochvernetzten und molekular geprägten Poly(acrylsäure)-Partikeln. Hierbei wurden unterschiedliche pharmakologische Wirkstoffe und Farbstoffe in die Partikel eingebracht, um deren Migrationsverhalten und Wiederanbindung an die Partikel zu untersuchen. Weiterhin wurden die Partikel erfolgreich in Zellaufnahmeexperimenten eingesetzt.

Toward stable N4-modified neurotensins for NTS1-receptor-targeted tumor imaging with 99mTc

A series of Gly-neurotensin(8-13) analogues modified at the N-terminus by acyclic tetraamines (Demotensin 1-4) were obtained by solid-phase peptide synthesis techniques. Strategic replacement of amino acids and/or reduction of sensitive peptide bonds were performed to enhance conjugate resistance against proteolytic enzymes. During 99mTc-labeling, single species radiopeptides, [99mTc]Demotensin 1-4, were easily obtained in high yields and typical specific activities of 1 Ci/micromol. Peptide conjugates displayed a high affinity binding to the human neurotensin subtype 1 receptor (NTS1-R) expressed in colon adenocarcinoma HT-29 or WiDr cells and/or in human tumor sections. [99mTc]Demotensin 1-4 internalized very rapidly in HT-29 or WiDr cells by a NTS1-R-mediated process. [99mTc]Demotensin 3 and 4, which remained stable during 1 h incubation in murine plasma, were selectively studied in nude mice bearing human HT-29 and WiDr xenografts. After injection, [99mTc]Demotensin 3 and 4 effectively and specifically localized in the experimental tumors and were rapidly excreted via the kidneys into the urine, exhibiting overall biodistribution patterns favorable for NTS1-R-targeted tumor imaging in man.

Future value based single assignment program representations and optimizations

An optimizing compiler internal representation fundamentally affects the clarity, efficiency and feasibility of optimization algorithms employed by the compiler. Static Single Assignment (SSA) as a state-of-the-art program representation has great advantages though still can be improved. This dissertation explores the domain of single assignment beyond SSA, and presents two novel program representations: Future Gated Single Assignment (FGSA) and Recursive Future Predicated Form (RFPF). Both FGSA and RFPF embed control flow and data flow information, enabling efficient traversal program information and thus leading to better and simpler optimizations. We introduce future value concept, the designing base of both FGSA and RFPF, which permits a consumer instruction to be encountered before the producer of its source operand(s) in a control flow setting. We show that FGSA is efficiently computable by using a series T1/T2/TR transformation, yielding an expected linear time algorithm for combining together the construction of the pruned single assignment form and live analysis for both reducible and irreducible graphs. As a result, the approach results in an average reduction of 7.7%, with a maximum of 67% in the number of gating functions compared to the pruned SSA form on the SPEC2000 benchmark suite. We present a solid and near optimal framework to perform inverse transformation from single assignment programs. We demonstrate the importance of unrestricted code motion and present RFPF. We develop algorithms which enable instruction movement in acyclic, as well as cyclic regions, and show the ease to perform optimizations such as Partial Redundancy Elimination on RFPF.

A feasible theory of truth over combinatory algebra

We define an applicative theory of truth TPT which proves totality exactly for the polynomial time computable functions. TPT has natural and simple axioms since nearly all its truth axioms are standard for truth theories over an applicative framework. The only exception is the axiom dealing with the word predicate. The truth predicate can only reflect elementhood in the words for terms that have smaller length than a given word. This makes it possible to achieve the very low proof-theoretic strength. Truth induction can be allowed without any constraints. For these reasons the system TPT has the high expressive power one expects from truth theories. It allows embeddings of feasible systems of explicit mathematics and bounded arithmetic. The proof that the theory TPT is feasible is not easy. It is not possible to apply a standard realisation approach. For this reason we develop a new realisation approach whose realisation functions work on directed acyclic graphs. In this way, we can express and manipulate realisation information more efficiently.

gems: An R Package for Simulating from Disease Progression Models

Mathematical models of disease progression predict disease outcomes and are useful epidemiological tools for planners and evaluators of health interventions. The R package gems is a tool that simulates disease progression in patients and predicts the effect of different interventions on patient outcome. Disease progression is represented by a series of events (e.g., diagnosis, treatment and death), displayed in a directed acyclic graph. The vertices correspond to disease states and the directed edges represent events. The package gems allows simulations based on a generalized multistate model that can be described by a directed acyclic graph with continuous transition-specific hazard functions. The user can specify an arbitrary hazard function and its parameters. The model includes parameter uncertainty, does not need to be a Markov model, and may take the history of previous events into account. Applications are not limited to the medical field and extend to other areas where multistate simulation is of interest. We provide a technical explanation of the multistate models used by gems, explain the functions of gems and their arguments, and show a sample application.