標(biāo)題: Titlebook: Knowledge Discovery and Emergent Complexity in Bioinformatics; First International Karl Tuyls,Ronald Westra,Ann Nowé Conference proceeding [打印本頁] 作者: sesamoiditis 時間: 2025-3-21 19:03
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics影響因子(影響力)
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics影響因子(影響力)學(xué)科排名
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics網(wǎng)絡(luò)公開度
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics被引頻次
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics被引頻次學(xué)科排名
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics年度引用
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics年度引用學(xué)科排名
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics讀者反饋
書目名稱Knowledge Discovery and Emergent Complexity in Bioinformatics讀者反饋學(xué)科排名
作者: LIMIT 時間: 2025-3-21 22:51
0302-9743 external stochastic uct- tions and chaos, process and additive noise, this machinery has been ticking for at least 3. 8 billion years. Yet, we may safely assum978-3-540-71036-3978-3-540-71037-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 推遲 時間: 2025-3-22 03:05 作者: 卷發(fā) 時間: 2025-3-22 06:13
Ronald Westra,Karl Tuyls,Yvan Saeys,Ann Nowéize likelihoods with respect to the usual Lebesgue measure of the data space, and (2) to bound the likelihood when its exact value is unattainable. We provide practical algorithms for these ideas and illustrate their use on synthetic data, images of digits and faces, as well as signals extracted fro作者: Hippocampus 時間: 2025-3-22 12:12
Ricardo Grau,Maria del C. Chavez,Robersy Sanchez,Eberto Morgado,Gladys Casas,Isis Bonetize likelihoods with respect to the usual Lebesgue measure of the data space, and (2) to bound the likelihood when its exact value is unattainable. We provide practical algorithms for these ideas and illustrate their use on synthetic data, images of digits and faces, as well as signals extracted fro作者: 商品 時間: 2025-3-22 14:50 作者: 偶然 時間: 2025-3-22 18:48 作者: archaeology 時間: 2025-3-23 01:10 作者: 2否定 時間: 2025-3-23 04:10 作者: periodontitis 時間: 2025-3-23 08:41
Yvan Saeys,Yves Van de Peerhe determinant as a sharpness function in an autofocus algorithm. We test the method on a large database of microscopy images with given ground truth focus results. We found that for a vast majority of the focus sequences the results are in the correct focal range. Cases where the algorithm fails ar作者: 監(jiān)禁 時間: 2025-3-23 11:41 作者: Harbor 時間: 2025-3-23 16:57 作者: 媒介 時間: 2025-3-23 19:51 作者: 咯咯笑 時間: 2025-3-24 02:03 作者: 推遲 時間: 2025-3-24 03:19
mation and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimiza978-3-030-80208-0978-3-030-80209-7Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: NICE 時間: 2025-3-24 08:53
ce, in July 2021..The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advan作者: 圓桶 時間: 2025-3-24 11:55
Ronald Westra,Karl Tuyls,Yvan Saeys,Ann Nowépace. One approach to find such a manifold is to estimate a Riemannian metric that locally models the given data. Data distributions with respect to this metric will then tend to follow the nonlinear structure of the data. In practice, the learned metric rely on parameters that are hand-tuned for a 作者: obsolete 時間: 2025-3-24 17:04 作者: fabricate 時間: 2025-3-24 19:40
Reinhard Guthke,Olaf Kniemeyer,Daniela Albrecht,Axel A. Brakhage,Ulrich M?llerf Information, GSI 2017,held in Paris, France, in November 2017...The 101 full papers presented were carefully reviewed and selected from 113 submissions and are organized into the following subjects: .statistics on non-linear data; shape space; optimal transport and applications: image processing; 作者: exceed 時間: 2025-3-25 00:15
Tero Harju,Chang Li,Ion Petre,Grzegorz Rozenbergpace. One approach to find such a manifold is to estimate a Riemannian metric that locally models the given data. Data distributions with respect to this metric will then tend to follow the nonlinear structure of the data. In practice, the learned metric rely on parameters that are hand-tuned for a 作者: 大吃大喝 時間: 2025-3-25 05:17 作者: 招待 時間: 2025-3-25 08:15 作者: 緊張過度 時間: 2025-3-25 14:51
Yvan Saeys,Yves Van de Peermore common Weibull or generalized extreme value distributions these distributions have at least two important advantages, the usage of the high threshold value assures that only the most important edge points enter the statistical analysis and the estimation is computationally more efficient since 作者: Affirm 時間: 2025-3-25 17:35
Susanne Toepfer,Reinhard Guthke,Dominik Driesch,Dirk Woetzel,Michael Pfaff additional properties: Lie groups, Quotient spaces, Stratified spaces etc? How can we describe the .? The structure of Quotient space in particular is widely used to model data, for example every time one deals with shape data. These can be shapes of constellations in Astronomy, shapes of human org作者: 認(rèn)為 時間: 2025-3-25 20:13 作者: 加入 時間: 2025-3-26 01:41
Peter Vrancx,Katja Verbeeck,Ann Nowés (PGA) and Geodesic PCA (GPCA) minimize the distance to a “Geodesic subspace”. This allows to build sequences of nested subspaces which are consistent with a forward component analysis approach. However, these methods cannot be adapted to a backward analysis and they are not symmetric in the parame作者: 慌張 時間: 2025-3-26 07:12
Knowledge Discovery and Emergent Complexity in Bioinformatics, College in Dublin, entitled “What Is Life? The Physical Aspect of the Living Cell and Mind”. In these lectures Schr?dinger stressed the fundamental differences encountered between observing animate and inanimate matter, and advanced some at the time audacious hypotheses about the nature and molecul作者: aesthetician 時間: 2025-3-26 12:20
Boolean Algebraic Structures of the Genetic Code: Possibilities of Applications,ductions have physico-chemical meaning. We summarize here that these algebraic structures can help us to describe the gene evolution process. Particularly in the experimental confrontation, it was found that most of the mutations of several proteins correspond to deductions in these algebras and the作者: 調(diào)整校對 時間: 2025-3-26 15:19
Discovery of Gene Regulatory Networks in ,,to cope with a dramatic change of environmental conditions, such as temperature shifts. Recently, gene expression data monitoring the stress response to a temperature shift from 30 °C to 48 °C was published. In the present work, these data were analyzed by reverse engineering to discover gene regula作者: 圓錐體 時間: 2025-3-26 17:02
Complexity Measures for Gene Assembly,oding blocks (called MDSs), shuffled and separated by non-coding sequences to form micronuclear genes. Assembling the coding blocks from micronuclear genes to form functional macronuclear genes is facilitated by an impressive in-vivo implementation of the linked list data structure of computer scien作者: babble 時間: 2025-3-26 22:28 作者: aspersion 時間: 2025-3-27 02:39
Advancing the State of the Art in Computational Gene Prediction, probabilistic, state-based generative models such as hidden Markov models and their various extensions. Unfortunately, little attention has been paid to the optimality of these models for the gene-parsing problem. Furthermore, as the prevalence of alternative splicing in human genes becomes more ap作者: HUSH 時間: 2025-3-27 07:41 作者: 咯咯笑 時間: 2025-3-27 10:41 作者: incite 時間: 2025-3-27 17:30 作者: Filibuster 時間: 2025-3-27 18:16
Analyzing Stigmergetic Algorithms Through Automata Games,ing for use in multi-agent systems, as it provides a simple framework for agent interaction and coordination. However, determining the global system behavior that will arise from local stigmergetic interactions is a complex problem. In this paper stigmergetic mechanisms are modeled using simple rein作者: 舊式步槍 時間: 2025-3-27 22:53
The Identification of Dynamic Gene-Protein Networks,h with special interest for partitioned state spaces. From the observation that the dynamics in natural systems tends to punctuated equilibria, we will focus on piecewise linear models and sparse and hierarchic interactions, as, for instance, described by Glass, Kauffman, and de Jong. Next, the pape作者: explicit 時間: 2025-3-28 05:27
Sparse Gene Regulatory Network Identification,od uses mixed . ./. . minimization: nonlinear least squares optimization to achieve an optimal fit between the model in state space form and the data, and . .-minimization of the parameter vector to find the sparsest such model possible. In this approach, in contrast to previous research, the dynami作者: Factual 時間: 2025-3-28 09:36
Boolean Algebraic Structures of the Genetic Code: Possibilities of Applications, acceptors in DNA sequences. Besides, pure mathematical models, Statistical techniques (Decision Trees) and Artificial Intelligence techniques (Bayesian Networks) were used in order to show how to accomplish them to solve these knowledge-discovery practical problems.作者: PON 時間: 2025-3-28 10:30
Discovery of Gene Regulatory Networks in ,,mining in the gene descriptions and evaluating gene ontology terms. The expression profiles of these genes were simulated by a differential equation system, whose structure and parameters were optimized minimizing both the number of non-vanishing parameters and the mean square error of model fit to the microarray data.作者: 漂白 時間: 2025-3-28 16:55 作者: 節(jié)省 時間: 2025-3-28 21:16
Advancing the State of the Art in Computational Gene Prediction,rove gene-finding accuracy both for human and non-human DNA clearly has a potential to significantly impact human health. In this paper we review current methods and suggest a number of possible directions for further research that may alleviate some of these problems and ultimately lead to better and more useful gene predictions.作者: 勤勞 時間: 2025-3-29 00:54
Knowledge Discovery and Emergent Complexity in Bioinformatics,ifferences encountered between observing animate and inanimate matter, and advanced some at the time audacious hypotheses about the nature and molecular structure of genes, some ten years before the discoveries of Watson and Crick.作者: 臆斷 時間: 2025-3-29 07:06
0302-9743 cs (KDECB 2006), held at the University of Ghent, Belgium, May 10, 2006. In February 1943, the Austrian physicist Erwin Schrodi ¨ nger, one of the founding fathers of quantum mechanics, gave a series of lectures at Trinity College in Dublin titled “What Is Life? The Physical Aspect of the Living Cel作者: 把…比做 時間: 2025-3-29 11:15
Enhancing Coding Potential Prediction for Short Sequences Using Complementary Sequence Features and a better prediction of coding potential in short sequences. To this end, we combine different, complementary sequence features together with a feature selection strategy. Results comparing the new classifiers to state of the art models show that our new approach significantly outperforms the existing methods when applied to short sequences.作者: KIN 時間: 2025-3-29 12:09
On the Neuronal Morphology-Function Relationship: A Synthetic Approach,gy and function. Our approach is implemented in a software tool and an experiment is presented. In the experiment we generate morphologies that approximate the functional properties of the .. We discuss the possibilities and limitations of our synthesized approach.作者: compel 時間: 2025-3-29 18:33 作者: 傷心 時間: 2025-3-29 20:07
Learning Relations from Biomedical Corpora Using Dependency Trees,hat recall is very important for the relation learning, we explored the ways of improving it. It has been shown that ensemble methods provide higher recall and precision than individual classifiers alone.
