On Designing Multicore-aware Simulators for Biological Systems

The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being computational expensive. We discuss the main opportunities to speed it up on multi-core platforms, which pose new challenges for parallelisation techniques. These opportunities are developed in two general families of solutions involving both the single simulation and a bulk of independent simulations (either replicas of derived from parameter sweep). Proposed solutions are tested on the parallelisation of the CWC simulator (Calculus of Wrapped Compartments) that is carried out according to proposed solutions by way of the FastFlow programming framework making possible fast development and efficient execution on multi-cores.Comment: 19 pages + cover pag

seqMINER: an integrated ChIP-seq data interpretation platform

In a single experiment, chromatin immunoprecipitation combined with high throughput sequencing (ChIP-seq) provides genome-wide information about a given covalent histone modification or transcription factor occupancy. However, time efficient bioinformatics resources for extracting biological meaning out of these gigabyte-scale datasets are often a limiting factor for data interpretation by biologists. We created an integrated portable ChIP-seq data interpretation platform called seqMINER, with optimized performances for efficient handling of multiple genome-wide datasets. seqMINER allows comparison and integration of multiple ChIP-seq datasets and extraction of qualitative as well as quantitative information. seqMINER can handle the biological complexity of most experimental situations and proposes methods to the user for data classification according to the analysed features. In addition, through multiple graphical representations, seqMINER allows visualization and modelling of general as well as specific patterns in a given dataset. To demonstrate the efficiency of seqMINER, we have carried out a comprehensive analysis of genome-wide chromatin modification data in mouse embryonic stem cells to understand the global epigenetic landscape and its change through cellular differentiation

Verifying Data Constraint Equivalence in FinTech Systems

Data constraints are widely used in FinTech systems for monitoring data consistency and diagnosing anomalous data manipulations. However, many equivalent data constraints are created redundantly during the development cycle, slowing down the FinTech systems and causing unnecessary alerts. We present EqDAC, an efficient decision procedure to determine the data constraint equivalence. We first propose the symbolic representation for semantic encoding and then introduce two light-weighted analyses to refute and prove the equivalence, respectively, which are proved to achieve in polynomial time. We evaluate EqDAC upon 30,801 data constraints in a FinTech system. It is shown that EqDAC detects 11,538 equivalent data constraints in three hours. It also supports efficient equivalence searching with an average time cost of 1.22 seconds, enabling the system to check new data constraints upon submission.Comment: 14 pages, 11 figures, accepted by ICSE 202

Anti-harassment training programmes in the RCMP: Is organizational transformative learning possible?

Examining a complex hierarchical law enforcement organization mandated anti-harassment (AH) training programmes. A sample of the RCMP revealed bullying negative behaviours occurring at 19% across study group (n=237). Mix-method approach using Kirkpatrick Evaluation, OCAI and NAQ-R provided insights into the correlation of training to organizational stated culture goals. More males reported being bullying (25%) No overt bullying reported by female respondents however, subtle bullying remains. All training materials aligned with organizational mission, vision and strategic goals. Curricula was clear however a gap exists between formal training and applied learning as evidenced by quantitative assessments. The NAQ-R (Cronbach alpha 0.777) indicates the presence of bullying but not at toxic levels. The OCAI highlights an overly hierarchical quadrant fulfilling market needs at the expense of clan and adhocracy quadrants. These findings support previous qualitative studies and employee engagement results. The leadership has choices to move forward and strengthen its AH training efforts

Constraint-based Run-time State Migration for Live Modeling

Live modeling enables modelers to incrementally update models as they are running and get immediate feedback about the impact of their changes. Changes introduced in a model may trigger inconsistencies between the model and its run-time state (e.g., deleting the current state in a statemachine); effectively requiring to migrate the run-time state to comply with the updated model. In this paper, we introduce an approach that enables to automatically migrate such runtime state based on declarative constraints defined by the language designer. We illustrate the approach using Nextep, a meta-modeling language for defining invariants and migration constraints on run-time state models. When a model changes, Nextep employs model finding techniques, backed by a solver, to automatically infer a new run-time model that satisfies the declared constraints. We apply Nextep to define migration strategies for two DSLs, and report on its expressiveness and performance

Constraint-based run-time state migration for live modeling

Live modeling enables modelers to incrementally update models as they are running and get immediate feedback about the impact of their changes. Changes introduced in a model may trigger inconsistencies between the model and its run-time state (e.g., deleting the current state in a statemachine); effectively requiring to migrate the run-time state to comply with the updated model. In this paper, we introduce an approach that enables to automatically migrate such runtime state based on declarative constraints defined by the language designer. We illustrate the approach using Nextep, a meta-modeling language for defining invariants and migration constraints on run-time state models. When a model changes, Nextep employs model finding techniques, backed by a solver, to automatically infer a new run-time model that satisfies the declared constraints. We apply Nextep to define migration strategies for two DSLs, and report on its expressiveness and performance