Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study

Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.

Removing redundancy for attribute implications in data with grades

Reasoning with if-then rules –in particular, with those taking from of implications between conjunctions of attributes– is crucial in many disciplines ranging from theoretical computer science to applications. One of the most important problems regarding the rules is to remove redundancies in order to obtain equivalent implicational sets with lower size.

Tecnología Nanopore para la secuenciación de DNA

Nanopore-based sequencer will open the path to the fourth-generation DNA sequencing technology. The main differences between this technique and the previous ones are: DNA molecule that will be sequenced does not need a previous amplification step, is not necessary any type of specific label both molecular adaptors, and it has been abolished enzymatic process in the nucleotide sequence identification event. These differences have as result a more economic method since don’t spend the necessary reagents for the previous techniques, furthermore it lets to sequence samples with a low DNA concentration. This technique is based in the use of a membrane with a biologic nanopore inserted in it whereby the molecule to analyze (analyte) it made to pass, this membrane is placed between two reservoirs containing ions, when an external volatage is applied in both sides this lead to an ion current through the nanopore. When an analyte cross the nanopore the ion current is modified, that modification in the amplitude and duration of ion current determine the physical and chemical properties of that analyte. By means of subsequent statistical analyzes it can be determined to what sequence own this ion current blockade patterns. More used nanopores are the biologic ones, although they are working to develop synthetic nanopores. The main biologic nanopores are: α-Hemolysin from Staphylococcus aureus (α-HL), Mycobacterium smegmatis porin A (MspA) and bacteriophage phi29 pore (phi29). Α-HL and MspA have in their narrowest point a diameter similar to nucleotide size, they are functional at high temperature both wide range of pH (2-12) but MspA is able to read four nucleotide at the same time while α- HL just can read one by one. Finally, phi29 present a bigger diameter what let to get information about DNA spatial conformation and their interaction with proteins (Feng et al., 2015). Nowaday Oxford Nanopore Technologies (ONT) is the only company which has developed Nanopore technology; they have two devices available to sequencing (PromethION and MinION). The MinION is a single-use DNA sequencing device with the size of a USB memory with a total of 3000 nanopores that can sequence until 200kb. The PrometheION is big size sequencer that own 48 different cells, what let to sequence different samples at the same time, with a total of 144.000 nanopores and reading of several megabases (https://www.nanoporetech.com/). The high processivity and low cost become this technique in a great option to massive- sequencing.