Hidden markov models
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Ebook "Introduction to computational biology: An evolutionary approach" Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models.
329p tracanhphuonghoa1007 22-04-2024 10 2 Download
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Nowadays, many applications uses speech recognition especially the field of computer science and electronics, Speech Recognition (SR) is the interpretation of words spoken into a text. It is also known as Speech-To-Text (STT) or Automatic-Speech-Recognition(ASR), or just Word-Recognition(WR). The HiddenMarkov-Model (HMM) is a type of Markov model, which means that the future state of the model depends on the current state, not on the entire history of the system and the goal of HMM is to learn a sequence of hidden states from a set of known states.
5p viritesh 02-04-2024 4 1 Download
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Knowing the activity of the mutational processes shaping a cancer genome may provide insight into tumorigenesis and personalized therapy. It is thus important to characterize the signatures of active mutational processes in patients from their patterns of single base substitutions.
12p vibransone 28-03-2024 9 2 Download
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Ebook "Introduction to mathematical methods in bioinformatics" looks at the mathematical foundations of the models currently in use. All existing books on bioinformatics are software-orientated and they concentrate on computer implementations of mathematical models of biology. This book is unique in the sense that it looks at the mathematical foundations of the models, which are crucial for correct interpretation of the outputs of the models.
305p tachieuhoa 28-01-2024 6 2 Download
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Ebook "Applied research in uncertainty modeling and analysis" is divided into six main sections. Part I (Chapters 1-4) presents the philosophical and theoretical foundation of uncertainty, new computational directions in neural networks, and some theoretical foundation of fuzzy systems. Part II (Chapters 5-8) reports on biomedical and chemical engineering applications.
547p loivantrinh 29-10-2023 3 2 Download
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This paper proposes a Multilayer Feed forward Neural Network (MLFNN) for speech classification in a smart electric wheelchair, in which with extraction of speech commands is performed using a Mel Frequency Cepstral Coefficients (MMFC) method.
7p vidoctorstrange 06-05-2023 7 4 Download
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The changing climate is altering timing of key fruit ripening processes and increasing the occurrence of fruit defects. To improve our understanding of the genetic control of raspberry fruit development an enhanced genetic linkage map was developed and used to examine ripening phenotypic data.
24p vihagrid 30-01-2023 6 4 Download
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In this paper, we propose a new method of vector quantization (VQ) performance optimally distribute VQ codebook components on Hidden Markov Model (HMM) state. This proposed method is carried out through two steps.
5p vilexus 05-10-2022 19 4 Download
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This paper describes the development and evaluation of a Vietnamese statistical speech synthesis system using the average voice approach. Although speaker-dependent systems have been applied extensively, no average voice based system has been developed for Vietnamese so far.
6p vichristinelagarde 04-07-2022 10 2 Download
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Part 1 of book "Speech and Language Processing: An introduction to natural language processing" provide with knowledge about: regular expressions and automata; words and transducers; N-grams; word classes and part-of-speech tagging; hidden markov and maximum entropy models; phonetics; speech synthesis; automatic speech recognition; speech recognition: advanced topics;...
509p britaikridanik 06-07-2022 35 3 Download
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Lecture Artificial Intelligence - Chapter 15a: Temporal probability models. The main contents of this chapter include all of the following: Time and uncertainty; Inference: filtering, prediction, smoothing; Hidden Markov models; Kalman filters (a brief mention); Dynamic Bayesian networks; Particle filtering.
39p cucngoainhan0 10-05-2022 11 2 Download
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A variety of methods have been developed to demultiplex pooled samples in a single cell RNA sequencing (scRNA-seq) experiment which either require hashtag barcodes or sample genotypes prior to pooling.
12p vielonmusk 30-01-2022 12 0 Download
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The iCLIP and eCLIP techniques facilitate the detection of protein–RNA interaction sites at high resolution, based on diagnostic events at crosslink sites. However, previous methods do not explicitly model the specifics of iCLIP and eCLIP truncation patterns and possible biases.
17p vialfrednobel 29-01-2022 9 0 Download
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We develop a novel computational method, NucHMM, to identify functional nucleosome states associated with cell type-specific combinatorial histone marks and nucleosome organization features such as phasing, spacing and positioning. We test it on publicly available MNase-seq and ChIP-seq data in MCF7, H1, and IMR90 cells and identify 11 distinct functional nucleosome states.
17p viarchimedes 26-01-2022 7 0 Download
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Whole-genome bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage.
14p vibeauty 23-10-2021 11 1 Download
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With the maturity of next generation sequencing technology, a huge amount of epigenomic data have been generated by several large consortia in the last decade. These plenty resources leave us the opportunity about sufficiently utilizing those data to explore biological problems.
13p viseulgi2711 31-08-2021 11 1 Download
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Trong bài báo này chúng tôi trình bày kết quả nghiên cứu đối với bài toán quan sát quỹ đạo đa mục tiêu MTT (Multiple Target Tracking). Cụ thể là phương pháp tiếp cận: dùng mô hình Markov ẩn HMM (Hidden Markov Model) để xác định mục tiêu trong MTT. Để xác định mục tiêu trong tập dữ liệu quan sát trong môi trường có nhiễu (có cả mục tiêu thực và mục tiêu giả), bài báo đã sử dụng ý tưởng thuật toán Viterbi (Viterbi Algorithm) trong HMM để xác định phần ẩn của mô hình, phần mục tiêu trong tập quan sát có nhiễu.
8p cothumenhmong12 08-07-2021 22 3 Download
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This paper considers an application of the Markov switching vector error correction model to the analysis of the long-run and the short-run dependence of Russian real GDP and real exchange on oil prices. An algorithm for estimation of the model with a priori information on a state of hidden Markov chain in some periods of time is provided.
11p caygaocaolon11 18-04-2021 21 2 Download
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A hidden Markov model (HMM) is a statistical model in which the system be- ing modeled is assumed to be a Markov process with unknown parameters. The challenge is to determine the hidden parameters from the observable parameters. Typically, the parameters of the model are given and the challenge is to find the most likely sequence of hidden states that could have generated a given sequence of observed states.
9p larachdumlanat126 31-12-2020 7 0 Download
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In studies of case-parent trios, we define copy number variants (CNVs) in the offspring that differs from the parental copy numbers as de novo and of interest for their potential functional role in disease. Among the leading array-based methods for discovery of de novo CNVs in case-parent trios is the joint hidden Markov model (HMM) implemented in the PennCNV software.
14p viwyoming2711 16-12-2020 12 1 Download