Process equivalence in the context of genetic mining

In various application domains there is a desire to compare process models, e.g., to relate an organization-specific process model to a reference model, to find a web service matching some desired service description, or to compare some normative process model with a process model discovered using process mining techniques. Although many researchers have worked on different notions of equivalence (e.g., trace equivalence, bisimulation, branching bisimulation, etc.), most of the existing notions are not very useful in this context. First of all, most equivalence notions result in a binary answer (i.e., two processes are equivalent or not). This is not very helpful, because, in real-life applications, one needs to differentiate between slightly different models and completely different models. Second, not all parts of a process model are equally important. There may be parts of the process model that are rarely activated (i.e., "process veins") while other parts are executed for most process instances (i.e., the "process arteries"). Clearly, differences in some veins of a process are less important than differences in the main artery of a process. To address the problem, this paper proposes a completely new way of comparing process models. Rather than directly comparing two models, the process models are compared with respect to some typical behavior. This way, we are able to avoid the two problems just mentioned. The approach has been implemented and has been used in the context of genetic process mining. Although the results are presented in the context of Petri nets, the approach can be applied to any process modeling language with executable semantics

Genetic diagnosis of familial hypercholesterolaemia: the importance of functional analysis of potential splice-site mutations

Familial hypercholesterolemia (FH) results from defective low-density lipoprotein receptor (LDLR) activity, mainly due to LDLR gene defects. Of the many different LDLR mutations found in patients with FH, about 6% of single base substitutions are located near or within introns, and are predicted to result in exon skipping, retention of an intron, or activation of cryptic sites during mRNA splicing. This paper reports on the Portuguese FH Study, which found 10 such mutations, 6 of them novel. For the mutations that have not been described before or those whose effect on function have not been analysed, their effect on splicing was investigated, using reverse transcriptase PCR analysis of LDLR mRNA from freshly isolated blood mononuclear cells. Two of these variants (c.313+6 T-->C, c.2389G-->T (p.V776L)) caused exon skipping, and one caused retention of an intron (c.1359-5C-->G), whereas two others (c.2140+5 G-->A and c.1061-8T-->C) had no apparent effect. Any effect of c.1185G-->C (p.V374V) on splicing could not be determined because it was on an allele with a promoter mutation (-42C-->G) that was probably not transcribed. Variants in four patients lost to follow-up could not be tested experimentally, but they almost certainly affect splicing because they disrupt the invariant AG or GT in acceptor (c.818-2A-->G) or donor (c.1060+1G-->A, c.1845+1delG and c.2547+1G-->A) spice sites. These findings emphasise that care must be taken before reporting the presence or absence of a splice-site mutation in the LDLR gene for diagnostic purposes. The study also shows that relatively simple, quick and inexpensive RNA assays can evaluate putative splicing mutations that are not always predictable by available software, thereby reducing genetic misdiagnosis of patients with FH

The need for a process mining evaluation framework in research and practice

Although there has been much progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we motivate the need for such an evaluation mechanism, and outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare the performance of their algorithms, and (b) end users to evaluate the validity of their process mining results

Towards an evaluation framework for process mining algorithms

Although there has been a lot of progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare the performance of their algorithms, and (b) end users to evaluate the validity of their process mining results. Furthermore, we describe two possible approaches to evaluate a discovered model (i) using existing comparison metrics that have been developed by the process mining research community, and (ii) based on the so-called k-fold-cross validation known from the machine learning community. To illustrate the application of these two approaches, we compared a set of models discovered by different algorithms based on a simple example log

Reprogramming the anti-tumor immune response via CRISPR genetic and epigenetic editing

Precise clustered regularly interspaced short palindromic repeats (CRISPR)-mediated genetic and epigenetic manipulation of the immune response has become a promising immunotherapeutic approach towards combating tumorigenesis and tumor progression. CRISPR-based immunologic reprograming in cancer therapy comprises the locus-specific enhancement of host immunity, the improvement of tumor immunogenicity and the suppression of tumor immunoevasion. To date, the ex vivo re-engineering of immune cells directed to inhibit the expression of immune checkpoints or to express synthetic immune receptors (chimeric antigen receptor therapy) has shown success in some settings, such as in the treatment of melanoma, lymphoma, liver and lung cancer. However, advancements in nuclease-deactivated CRISPR-associated nuclease-9 (dCas9)-mediated transcriptional activation or repression and Cas13-directed gene suppression presents novel avenues for the development of tumor immunotherapies. In this review, the basis for development, mechanism of action and outcomes from recently published Cas9-based clinical trial (genetic editing) and dCas9/Cas13-based pre-clinical (epigenetic editing) data are discussed. Lastly, we review cancer immunotherapy-specific considerations and barriers surrounding use of these approaches in the clinic

Familial hypercholesterolaemia in Portugal

Familial hypercholesterolaemia (FH) is characterised clinically by an increased level of circulating LDL cholesterol that leads to lipid accumulation in tendons and arteries, premature atherosclerosis and increased risk of coronary heart disease (CHD). Although Portugal should have about 20,000 cases, this disease is severely under-diagnosed in our country, this being the first presentation of Portuguese data on FH. A total of 602 blood samples were collected from 184 index patients and 418 relatives from several centres throughout Portugal. Fifty-three different mutations were found in 83 index patients, 79 heterozygous and 4 with two defective LDLR alleles. Additionally, 4 putative alterations were found in 8 patients but were not considered mutations causing disease, mainly because they did not co-segregate with hypercholesterolaemia in the families. Three unrelated patients were found to be heterozygous for the APOB(3500) mutation and two unrelated patients were found to be heterozygous for a novel mutation in PCSK9, predicted to cause a single amino acid substitution, D374H. Cascade screening increased the number of FH patients identified genetically to 204. The newly identified FH patients are now receiving counselling and treatment based on the genetic diagnosis. The early identification of FH patients can increase their life expectancy and quality of life by preventing the development of premature CHD if patients receive appropriate pharmacological treatment