Learning from the past with experiment databases

Thousands of Machine Learning research papers contain experimental comparisons that usually have been conducted with a single focus of interest, and detailed results are usually lost after publication. Once past experiments are collected in experiment databases they allow for additional and possibly much broader investigation. In this paper, we show how to use such a repository to answer various interesting research questions about learning algorithms and to verify a number of recent studies. Alongside performing elaborate comparisons and rankings of algorithms, we also investigate the effects of algorithm parameters and data properties, and study the learning curves and bias-variance profiles of algorithms to gain deeper insights into their behavior

Inductive queries for a drug designing robot scientist

It is increasingly clear that machine learning algorithms need to be integrated in an iterative scientific discovery loop, in which data is queried repeatedly by means of inductive queries and where the computer provides guidance to the experiments that are being performed. In this chapter, we summarise several key challenges in achieving this integration of machine learning and data mining algorithms in methods for the discovery of Quantitative Structure Activity Relationships (QSARs). We introduce the concept of a robot scientist, in which all steps of the discovery process are automated; we discuss the representation of molecular data such that knowledge discovery tools can analyse it, and we discuss the adaptation of machine learning and data mining algorithms to guide QSAR experiments

A Community-Based Platform for Machine Learning Experimentation

We demonstrate the practical uses of a community-based platform for the sharing and in-depth investigation of the thousands of machine learning experiments executed every day. It is aimed at researchers and practitioners of data mining techniques, and is publicly available at http://expdb.cs.kuleuven.be. The system offers standards and API’s for sharing experimental results, extensive querying capabilities of the gathered results and allows easy integration in existing data mining toolboxes. We believe such a system may speed up scientific discovery and enhance the scientific rigor of machine learning research.status: publishe

S.cerevisiae Complex Function Prediction with Modular Multi-Relational Framework

Proceeding of: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Córdoba, Spain, June 1-4, 2010Determining the functions of genes is essential for understanding how the metabolisms work, and for trying to solve their malfunctions. Genes usually work in groups rather than isolated, so functions should be assigned to gene groups and not to individual genes. Moreover, the genetic knowledge has many relations and is very frequently changeable. Thus, a propositional ad-hoc approach is not appropriate to deal with the gene group function prediction domain. We propose the Modular Multi-Relational Framework (MMRF), which faces the problem from a relational and flexible point of view. The MMRF consists of several modules covering all involved domain tasks (grouping, representing and learning using computational prediction techniques). A specific application is described, including a relational representation language, where each module of MMRF is individually instantiated and refined for obtaining a prediction under specific given conditions.This research work has been supported by CICYT, TRA 2007-67374-C02-02 project and by the expert biological knowledge of the Structural Computational Biology Group in Spanish National Cancer Research Centre (CNIO). The authors would like to thank members of Tilde tool developer group in K.U.Leuven for providing their help and many useful suggestions.Publicad

Should We Continue to Measure Endometrial Thickness in Modern-Day Medicine? The Effect on Live Birth Rates and Birth Weight

The evaluation of endometrial thickness (EMT) is still part of standard cycle monitoring during IVF, despite the lack of robust evidence of any value of this measurement to predict little revalidation in contemporary medical practice; other tools, however, such as endocrine profile monitoring, have become increasingly popular. The aim of this study was to reassess whether EMT affects the outcome of a fresh embryo transfer in modern-day medicine, using a retrospective, single-centre cohort of 3350 IVF cycles (2827 women) carried out between 2010 and 2014. In the multivariate regression analysis, EMT was non-linearly associated with live birth, with live birth rates being the lowest with an EMT less than 7.0 mm (21.6%; P < 0.001) and then between 7.0 mm and 9.0 mm (30.2%; P = 0.008). An EMT less than 7.0 mm was also associated with a decrease in neonatal birthweight z-scores (-0.40; 95% CI -0.69 to -0.12). In conclusion, these results reaffirm the use of EMT as a potential prognostic tool for live birth rates and neonatal birthweight in contemporary IVF, namely when considered together with other ovarian stimulation monitoring methods, such as the late-follicular endocrine profile.info:eu-repo/semantics/publishedVersio

Predicting gene function using hierarchical multi-label decision tree ensembles

<p>Abstract</p> <p>Background</p> <p><it>S. cerevisiae</it>, <it>A. thaliana </it>and <it>M. musculus </it>are well-studied organisms in biology and the sequencing of their genomes was completed many years ago. It is still a challenge, however, to develop methods that assign biological functions to the ORFs in these genomes automatically. Different machine learning methods have been proposed to this end, but it remains unclear which method is to be preferred in terms of predictive performance, efficiency and usability.</p> <p>Results</p> <p>We study the use of decision tree based models for predicting the multiple functions of ORFs. First, we describe an algorithm for learning hierarchical multi-label decision trees. These can simultaneously predict all the functions of an ORF, while respecting a given hierarchy of gene functions (such as FunCat or GO). We present new results obtained with this algorithm, showing that the trees found by it exhibit clearly better predictive performance than the trees found by previously described methods. Nevertheless, the predictive performance of individual trees is lower than that of some recently proposed statistical learning methods. We show that ensembles of such trees are more accurate than single trees and are competitive with state-of-the-art statistical learning and functional linkage methods. Moreover, the ensemble method is computationally efficient and easy to use.</p> <p>Conclusions</p> <p>Our results suggest that decision tree based methods are a state-of-the-art, efficient and easy-to-use approach to ORF function prediction.</p

An in vivo culture system for human embryos using an encapsulation technology: a pilot study

BACKGROUND Animal studies have demonstrated better embryo development in vivo than in vitro. This pilot study tested the feasibility of using a novel in utero culture system (IUCS) to obtain normal human fertilization and embryo development. METHODS The IUCS device comprised a perforated silicone hollow tube. The study included 13 patients (<36 years) undergoing a first intracytoplasmic sperm injection (ICSI) treatment and 167 metaphase II oocytes in three groups. In Group 1, 1-2 h after ICSI, sibling oocytes were assigned to IUCS or conventional in vitro culture. The device was retrieved on Day 1, and all zygotes were cultured in vitro till Day 5. In Group 2, fertilized oocytes were assigned on Day 1, embryos retrieved on Day 3 and all embryos cultured till Day 5. In Group 3, after Day 0 assignment, embryos were retrieved on Day 3 for blastomere biopsy and fluorescence in situ hybridization (FISH) and cultured until Day 5. The highest quality blastocysts were transferred on Day 5. RESULTS Fertilization and embryo development were comparable in the in vitro and IUCS arms, with a tendency towards better embryo quality in the IUCS. FISH analysis in Group 3 revealed more normal embryos using the IUCS (P = 0.049). Three clinical pregnancies and live births were obtained: two from the IUCS arm and one from the in vitro arm. CONCLUSIONS Our pilot study shows that this new IUCS appears to be feasible and safe, supporting normal fertilization, embryo development and normal chromosomal segregation. Furthermore, live births are possible after the transient presence of a silicone device in the uterus.Clinicaltrials.gov: NCT0048010

How different experimental models of secondary hyperalgesia change the nociceptive flexion reflex

In this neurophysiological study in healthy humans, we assessed how central sensitization induced by either high-frequency stimulation (HFS) or topical capsaicin application modulates features of the RIII reflex response. The ability of these stimuli to engage the endogenous pain modulatory system was also tested. In 26 healthy participants we elicited an RIII reflex using suprathreshold stimulation of the sural nerve. Subsequently HFS or capsaicin were applied to the foot and the RIII reflex repeated after 15 minutes. Contact heating of the volar forearm served as the heterotopic test stimulus to probe activation of the endogenous pain modulatory system. HFS significantly reduced the pain threshold by 29% and the RIII reflex threshold by 20%. Capsaicin significantly reduced the pain threshold by 17% and the RIII reflex threshold by 18%. Both HFS and capsaicin left RIII reflex size unaffected. Numerical Rating Scale (NRS) pain scores elicited by the heterotopic noxious heat stimulus were unaffected by capsaicin and slightly increased by HFS. HFS and capsaicin similarly modulated the pain threshold and RIII reflex threshold, without a concomitant inhibitory effect of the endogenous pain modulatory system. Our neurophysiological study supports the use of the RIII reflex in investigating central sensitization in humans

Improving the efficiency of ILP systems

Inductive Logic Programming (ILP) is a promising technol-ogy for knowledge extraction applications. ILP has produced intelligiblesolutions for a wide variety of domains where it has been applied. TheILP lack of eciency is, however, a major impediment for its scalabilityto applications requiring large amounts of data. In this paper we pro-pose a set of techniques that improve ILP systems eciency and makethen more likely to scale up to applications of knowledge extraction fromlarge datasets. We propose and evaluate the lazy evaluation of examples,to improve the eciency of ILP systems. Lazy evaluation is essentiallya way to avoid or postpone the evaluation of the generated hypotheses(coverage tests).The techniques were evaluated using the IndLog system on ILP datasetsreferenced in the literature. The proposals lead to substantial eficiencyimprovements and are generally applicable to any ILP system

An in vivo culture system for human embryos using an encapsulation technology: a pilot study

ACKGROUND: Animal studies have demonstrated better embryo development in vivo than in vitro. This pilot study tested the feasibility of using a novel in utero culture system (IUCS) to obtain normal human fertilization and embryo development. METHODS: The IUCS device comprised a perforated silicone hollow tube. The study included 13 patients (<36 years) undergoing a first intracytoplasmic sperm injection (ICSI) treatment and 167 metaphase II oocytes in three groups. In Group 1, 1-2 h after ICSI, sibling oocytes were assigned to IUCS or conventional in vitro culture. The device was retrieved on Day 1, and all zygotes were cultured in vitro till Day 5. In Group 2, fertilized oocytes were assigned on Day 1, embryos retrieved on Day 3 and all embryos cultured till Day 5. In Group 3, after Day 0 assignment, embryos were retrieved on Day 3 for blastomere biopsy and fluorescence in situ hybridization (FISH) and cultured until Day 5. The highest quality blastocysts were transferred on Day 5. RESULTS: Fertilization and embryo development were comparable in the in vitro and IUCS arms, with a tendency towards better embryo quality in the IUCS. FISH analysis in Group 3 revealed more normal embryos using the IUCS (P = 0.049). Three clinical pregnancies and live births were obtained: two from the IUCS arm and one from the in vitro arm. CONCLUSIONS: Our pilot study shows that this new IUCS appears to be feasible and safe, supporting normal fertilization, embryo development and normal chromosomal segregation. Furthermore, live births are possible after the transient presence of a silicone device in the uterus. Clinicaltrials.gov: NCT00480103