Extended Finite-State Machine Induction Using SAT-Solver.

Abstract-In the paper we describe the extended finite-state machine (EFSM) induction method that uses SAT-solver. Input data for the induction algorithm is a set of test scenarios. The algorithm consists of several steps: scenarios tree construction, compatibility graph construction, Boolean formula construction, SAT-solver invocation and finite-state machine construction from satisfying assignment. These extended finite-state machines can be used in automata-based programming, where programs are designed as automated controlled objects. Each automated controlled object contains a finite-state machine and a controlled object. The method described has been tested on randomly generated scenario sets of size from 250 to 2000 and on the alarm clock controlling EFSM induction problem where it has greatly outperformed genetic algorithm

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

Background: The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results: In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions: Many current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another

Test-Based Extended Finite-State Machines Induction with Evolutionary Algorithms and Ant Colony Optimization

ABSTRACT In this paper we consider the problem of extended finite-state machines induction. The input data for this problem is a set of tests. Each test consists of two sequences -an input sequence and a corresponding output sequence. We present a new method of Extended Finite-State Machines (EFSM) induction based on an Ant Colony Optimization algorithm (ACO) and a new meaningful test-based crossover operator for EFSMs. New algorithms are compared with a genetic algorithm (GA) using a traditional crossover, a (1+1) evolutionary strategy and a random mutation hill climber. This comparison shows that the use of test-based crossover greatly improves performance of GA. GA on average also significantly outperforms the hill climber and evolutionary strategy. ACO outperforms GA, and the difference between average performance of ACO and GA hybridized with hill climber is insignificant

Water pollution monitoring by an artificial sensory system performing in terms of Vibrio fischeri bacteria

This report describes the application of potentiometric multisensory system for estimation of water samples toxicity in terms of Microtox ® analyzer—a widespread instrument for toxicity evaluation. The working principle of Microtox ® analyser is based on a registration of luminescence from Vibrio fischeri bacteria. This luminescence depends on metabolism conditions and toxicity of the environment. Due to the fact that metabolism is influenced by multiple parameters the method is associated with certain limitations. Unlike this bioassay procedure the employment of multisensory system does not require the use of living organisms and can provide for faster toxicity evaluation. Fifty-five real and model polluted water samples, for which the toxicity was established by bioassay, were studied. The response of multisensory array processed with machine learning techniques allows for prediction of toxicity in terms of EC50 with relative errors of 20–25%. Taking into account the complexity of the task (simulation of complex biological reactions with inanimate instrument) this can be considered as a good promise for further research in this direction in order to develop instrumental alternative for toxicity assessmen

Water pollution monitoring by an artificial sensory system performing in terms of Vibrio fischeri bacteria

This report describes the application of potentiometric multisensory system for estimation of water samples toxicity in terms of Microtox ® analyzer—a widespread instrument for toxicity evaluation. The working principle of Microtox ® analyser is based on a registration of luminescence from Vibrio fischeri bacteria. This luminescence depends on metabolism conditions and toxicity of the environment. Due to the fact that metabolism is influenced by multiple parameters the method is associated with certain limitations. Unlike this bioassay procedure the employment of multisensory system does not require the use of living organisms and can provide for faster toxicity evaluation. Fifty-five real and model polluted water samples, for which the toxicity was established by bioassay, were studied. The response of multisensory array processed with machine learning techniques allows for prediction of toxicity in terms of EC50 with relative errors of 20–25%. Taking into account the complexity of the task (simulation of complex biological reactions with inanimate instrument) this can be considered as a good promise for further research in this direction in order to develop instrumental alternative for toxicity assessmen

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

International audienceBackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another