Multivariate Algorithmics In Biological Data Analysis

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Multivariate Algorithmics In Biological Data Analysis

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Author : Johannes Uhlmann
language : en
Publisher:
Release Date : 2011

Multivariate Algorithmics In Biological Data Analysis written by Johannes Uhlmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.

Parameterized Algorithmics For Network Analysis Clustering Querying

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Author : Christian Komusiewicz
language : en
Publisher: Univerlagtuberlin
Release Date : 2011

Parameterized Algorithmics For Network Analysis Clustering Querying written by Christian Komusiewicz and has been published by Univerlagtuberlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.

Fine Grained Complexity Analysis Of Some Combinatorial Data Science Problems

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Author : Froese, Vincent
language : en
Publisher: Universitätsverlag der TU Berlin
Release Date : 2018-10-10

Fine Grained Complexity Analysis Of Some Combinatorial Data Science Problems written by Froese, Vincent and has been published by Universitätsverlag der TU Berlin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-10 with Computers categories.

This thesis is concerned with analyzing the computational complexity of NP-hard problems related to data science. For most of the problems considered in this thesis, the computational complexity has not been intensively studied before. We focus on the complexity of computing exact problem solutions and conduct a detailed analysis identifying tractable special cases. To this end, we adopt a parameterized viewpoint in which we spot several parameters which describe properties of a specific problem instance that allow to solve the instance efficiently. We develop specialized algorithms whose running times are polynomial if the corresponding parameter value is constant. We also investigate in which cases the problems remain intractable even for small parameter values. We thereby chart the border between tractability and intractability for some practically motivated problems which yields a better understanding of their computational complexity. In particular, we consider the following problems. General Position Subset Selection is the problem to select a maximum number of points in general position from a given set of points in the plane. Point sets in general position are well-studied in geometry and play a role in data visualization. We prove several computational hardness results and show how polynomial-time data reduction can be applied to solve the problem if the sought number of points in general position is very small or very large. The Distinct Vectors problem asks to select a minimum number of columns in a given matrix such that all rows in the selected submatrix are pairwise distinct. This problem is motivated by combinatorial feature selection. We prove a complexity dichotomy with respect to combinations of the minimum and the maximum pairwise Hamming distance of the rows for binary input matrices, thus separating polynomial-time solvable from NP-hard cases. Co-Clustering is a well-known matrix clustering problem in data mining where the goal is to partition a matrix into homogenous submatrices. We conduct an extensive multivariate complexity analysis revealing several NP-hard and some polynomial-time solvable and fixed-parameter tractable cases. The generic F-free Editing problem is a graph modification problem in which a given graph has to be modified by a minimum number of edge modifications such that it does not contain any induced subgraph isomorphic to the graph F. We consider three special cases of this problem: The graph clustering problem Cluster Editing with applications in machine learning, the Triangle Deletion problem which is motivated by network cluster analysis, and Feedback Arc Set in Tournaments with applications in rank aggregation. We introduce a new parameterization by the number of edge modifications above a lower bound derived from a packing of induced forbidden subgraphs and show fixed-parameter tractability for all of the three above problems with respect to this parameter. Moreover, we prove several NP-hardness results for other variants of F-free Editing for a constant parameter value. The problem DTW-Mean is to compute a mean time series of a given sample of time series with respect to the dynamic time warping distance. This is a fundamental problem in time series analysis the complexity of which is unknown. We give an exact exponential-time algorithm for DTW-Mean and prove polynomial-time solvability for the special case of binary time series. Diese Dissertation befasst sich mit der Analyse der Berechnungskomplexität von NP-schweren Problemen aus dem Bereich Data Science. Für die meisten der hier betrachteten Probleme wurde die Berechnungskomplexität bisher nicht sehr detailliert untersucht. Wir führen daher eine genaue Komplexitätsanalyse dieser Probleme durch, mit dem Ziel, effizient lösbare Spezialfälle zu identifizieren. Zu diesem Zweck nehmen wir eine parametrisierte Perspektive ein, bei der wir bestimmte Parameter definieren, welche Eigenschaften einer konkreten Probleminstanz beschreiben, die es ermöglichen, diese Instanz effizient zu lösen. Wir entwickeln dabei spezielle Algorithmen, deren Laufzeit für konstante Parameterwerte polynomiell ist. Darüber hinaus untersuchen wir, in welchen Fällen die Probleme selbst bei kleinen Parameterwerten berechnungsschwer bleiben. Somit skizzieren wir die Grenze zwischen schweren und handhabbaren Probleminstanzen, um ein besseres Verständnis der Berechnungskomplexität für die folgenden praktisch motivierten Probleme zu erlangen. Beim General Position Subset Selection Problem ist eine Menge von Punkten in der Ebene gegeben und das Ziel ist es, möglichst viele Punkte in allgemeiner Lage davon auszuwählen. Punktmengen in allgemeiner Lage sind in der Geometrie gut untersucht und spielen unter anderem im Bereich der Datenvisualisierung eine Rolle. Wir beweisen etliche Härteergebnisse und zeigen, wie das Problem mittels Polynomzeitdatenreduktion gelöst werden kann, falls die Anzahl gesuchter Punkte in allgemeiner Lage sehr klein oder sehr groß ist. Distinct Vectors ist das Problem, möglichst wenige Spalten einer gegebenen Matrix so auszuwählen, dass in der verbleibenden Submatrix alle Zeilen paarweise verschieden sind. Dieses Problem hat Anwendungen im Bereich der kombinatorischen Merkmalsselektion. Wir betrachten Kombinationen aus maximalem und minimalem paarweisen Hamming-Abstand der Zeilenvektoren und beweisen eine Komplexitätsdichotomie für Binärmatrizen, welche die NP-schweren von den polynomzeitlösbaren Kombinationen unterscheidet. Co-Clustering ist ein bekanntes Matrix-Clustering-Problem aus dem Gebiet Data-Mining. Ziel ist es, eine Matrix in möglichst homogene Submatrizen zu partitionieren. Wir führen eine umfangreiche multivariate Komplexitätsanalyse durch, in der wir zahlreiche NP-schwere, sowie polynomzeitlösbare und festparameterhandhabbare Spezialfälle identifizieren. Bei F-free Editing handelt es sich um ein generisches Graphmodifikationsproblem, bei dem ein Graph durch möglichst wenige Kantenmodifikationen so abgeändert werden soll, dass er keinen induzierten Teilgraphen mehr enthält, der isomorph zum Graphen F ist. Wir betrachten die drei folgenden Spezialfälle dieses Problems: Das Graph-Clustering-Problem Cluster Editing aus dem Bereich des Maschinellen Lernens, das Triangle Deletion Problem aus der Netzwerk-Cluster-Analyse und das Problem Feedback Arc Set in Tournaments mit Anwendungen bei der Aggregation von Rankings. Wir betrachten eine neue Parametrisierung mittels der Differenz zwischen der maximalen Anzahl Kantenmodifikationen und einer unteren Schranke, welche durch eine Menge von induzierten Teilgraphen bestimmt ist. Wir zeigen Festparameterhandhabbarkeit der drei obigen Probleme bezüglich dieses Parameters. Darüber hinaus beweisen wir etliche NP-Schwereergebnisse für andere Problemvarianten von F-free Editing bei konstantem Parameterwert. DTW-Mean ist das Problem, eine Durchschnittszeitreihe bezüglich der Dynamic-Time-Warping-Distanz für eine Menge gegebener Zeitreihen zu berechnen. Hierbei handelt es sich um ein grundlegendes Problem der Zeitreihenanalyse, dessen Komplexität bisher unbekannt ist. Wir entwickeln einen exakten Exponentialzeitalgorithmus für DTW-Mean und zeigen, dass der Spezialfall binärer Zeitreihen in polynomieller Zeit lösbar ist.

Revealing Uncharted Biology With Single Cell Multiplex Proteomic Technologies

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Author : Wendy Fantl
language : en
Publisher: Academic Press
Release Date : 2024-06-25

Revealing Uncharted Biology With Single Cell Multiplex Proteomic Technologies written by Wendy Fantl and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-25 with Science categories.

Revealing Uncharted Biology with Single Cell Multiplex Proteomic Technologies: ApplicationsHealthy tissues and organs rely on the precise coordination of diverse cell types, each responding to external and internal signals. Disease disrupts this coordination. Since proteins drive cellular function, analyzing their abundance and activation states in single cells helps identify key cell populations in health and disease. Bulk protein analyses mask critical differences between individual cells. Additionally, the arrangement of cells into neighborhoods through cell-cell interactions is essential for tissue function. Over the last decade, single-cell proteomic phenotyping combined with positional information has become crucial for understanding biology in health and disease. This has led to the development of multiple technology platforms, profoundly impacting fields including developmental biology, cancer biology, immunology, neuroscience, and drug discovery. This book focuses on the application of single-cell multiplex proteomic platforms to various biological systems. These platforms have proved to be essential in biomedical research, advancing our understanding of complex biological systems at the cellular level. Compelling studies where authors use these technologies to answer previously unanswerable questions are featured. Exploring this "Uncharted Biology" opens new avenues for scientific inquiry and clinical translation, covering areas including oncology, immunology, metabolomics, stem cell research, preclinical models, and translational research. The initial chapters discuss incorporating these technologies into core facilities and consortia, providing access for multiple users and integrating datasets from other omics technologies. The following chapters cover applications in diverse areas such as muscle stem cell function in skeletal muscle regeneration, metabolic regulome profiling, translational studies, developing predictive biomarkers for patients receiving immune checkpoint inhibitors, and pre-clinical studies of lung cancer. These applications demonstrate how advanced single cell proteomic technologies are reshaping our understanding of complex biological systems and enhancing clinical translation. Revealing Uncharted Biology with Single Cell Multiplex Proteomic Technologies: Applications highlights the transformative benefits of single-cell proteomics, offering insights into cellular mechanisms underlying health and disease and inspiring further exploration into "Uncharted Biology." It is an essential resource for researchers, clinicians, and students aiming to advance biomedical science and improve therapeutic outcomes. - Provides insights into the path to success of key research articles based on Multiplex Single-Cell analysis techniques results - Contains detailed method information - Discusses strengths and limitations of techniques applied to each research domain covered - Includes discussions on the failures encountered along the research path and how to avoid them

Mathematical Foundations Of Computer Science 2012

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Author : Branislav Rovan
language : en
Publisher: Springer
Release Date : 2012-08-01

Mathematical Foundations Of Computer Science 2012 written by Branislav Rovan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-01 with Computers categories.

This volume constitutes the refereed proceedings of the 37th International Symposium on Mathematical Foundations of Computer Science, MFCS 2012, held in Bratislava, Slovakia, in August 2012. The 63 revised full papers presented together with 8 invited talks were carefully reviewed and selected from 162 submissions. Topics covered include algorithmic game theory, algorithmic learning theory, algorithms and data structures, automata, formal languages, bioinformatics, complexity, computational geometry, computer-assisted reasoning, concurrency theory, databases and knowledge-based systems, foundations of computing, logic in computer science, models of computation, semantics and verification of programs, and theoretical issues in artificial intelligence.

One And Two Dimensional Nanomaterials

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Author : Sanket Joshi
language : en
Publisher: Academic Press
Release Date : 2025-06-13

One And Two Dimensional Nanomaterials written by Sanket Joshi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-13 with Technology & Engineering categories.

One- and Two- Dimensional Nanomaterials: Bioengineering Applications covers in-depth information on the properties, structures, and preparation methods of one- and two- dimensional nanomaterials, providing readers with tools that can be immediately implemented and adapted to fit a diverse range of applications.The first part of the book covers the fundamentals of these materials, including properties and synthesis techniques. The second part of the book focuses on the use of several conventional and emerging nanomaterials in the areas of pollution management, remediation practices, and other possible applications in biosensing, biomedicine, and antimicrobial activity.This book will be a helpful resource to nano-scientists, biotechnologists, and bioengineers engaged in studying the emerging trends and different fabrication techniques of nanostructures and their applications and possible toxicity. - Covers applications of one- and two- dimensional nanomaterials on various fields, including biomedical engineering, energy generation, pollution remediation, and more - Discusses the toxic side effects of chemically or physically synthesized nanomaterials - Incorporates relevant case studies to increase understanding

Encyclopedia Of Bioinformatics And Computational Biology

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Author :
language : en
Publisher: Elsevier
Release Date : 2018-08-21

Encyclopedia Of Bioinformatics And Computational Biology written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Medical categories.

Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Software Tools And Algorithms For Biological Systems

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Author : Hamid Arabnia
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-23

Software Tools And Algorithms For Biological Systems written by Hamid Arabnia and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-23 with Computers categories.

“Software Tools and Algorithms for Biological Systems" is composed of a collection of papers received in response to an announcement that was widely distributed to academicians and practitioners in the broad area of computational biology and software tools. Also, selected authors of accepted papers of BIOCOMP’09 proceedings (International Conference on Bioinformatics and Computational Biology: July 13-16, 2009; Las Vegas, Nevada, USA) were invited to submit the extended versions of their papers for evaluation.

Intelligent Multidimensional Data Clustering And Analysis

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Author : Bhattacharyya, Siddhartha
language : en
Publisher: IGI Global
Release Date : 2016-11-29

Intelligent Multidimensional Data Clustering And Analysis written by Bhattacharyya, Siddhartha and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-29 with Computers categories.

Data mining analysis techniques have undergone significant developments in recent years. This has led to improved uses throughout numerous functions and applications. Intelligent Multidimensional Data Clustering and Analysis is an authoritative reference source for the latest scholarly research on the advantages and challenges presented by the use of cluster analysis techniques. Highlighting theoretical foundations, computing paradigms, and real-world applications, this book is ideally designed for researchers, practitioners, upper-level students, and professionals interested in the latest developments in cluster analysis for large data sets.

Advances In Multivariate Statistical Methods

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Author : Ashis Sengupta
language : en
Publisher: World Scientific
Release Date : 2009-06-23

Advances In Multivariate Statistical Methods written by Ashis Sengupta and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-23 with Mathematics categories.

This volume contains a collection of research articles on multivariate statistical methods, encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. It serves as a tribute to Professor S N Roy, an eminent statistician who has made seminal contributions to the area of multivariate statistical methods, on his birth centenary. In the area of emerging applications, the topics include bioinformatics, categorical data and clinical trials, econometrics, longitudinal data analysis, microarray data analysis, sample surveys, statistical process control, etc.Researchers, professionals and advanced graduates will find the book an essential resource for modern developments in theory as well as for innovative and emerging important applications in the area of multivariate statistical methods.