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MiniDBG: A Novel and Minimal De Bruijn Graph for Read Mapping

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND bioinformatics 2024年第1期21卷 129-142页

作者： Yu, Changyong Zhao, Yuhai Zhao, Chu Jin, Jianyu Mao, Keming Wang, Guoren Northeastern Univ Coll Comp Sci & Engn Shenyang 110819 Peoples R China Beijing Inst Technol Sch Comp Sci & Technol Beijing 100081 Peoples R China

The De Bruijn graph (DBG) has been widely used in the algorithms for indexing or organizing read and reference sequences in bioinformatics. However, a DBG model that can locate each node, edge and path on sequence has not been proposed so far. Recently, DBG has been used for representing reference sequences in read mapping tasks. In this process, it is not a one-to-one correspondence between the paths of DBG and the substrings of reference sequence. This results in the false path on DBG, which means no substrings of reference producing the path. Moreover, if a candidate path of a read is true, we need to locate it and verify the candidate on sequence. To solve these problems, we proposed a DBG model, called MiniDBG, which stores the position lists of a minimal set of edges. With the position lists, MiniDBG can locate any node, edge and path efficiently. We also proposed algorithms for generating MiniDBG based on an original DBG and algorithms for locating edges or paths on sequence. We designed and ran experiments on real datasets for comparing them with BWT-based and position list-based methods. The experimental results show that MiniDBG can locate the edges and paths efficiently with lower memory costs.

关键词： bioinformatics Genomics Indexing Costs Task analysis Memory management Data structures Graph algorithms Indexing methods bioinformatics databases Queries

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ChemMine. A compound mining database for chemical genomics

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PLANT PHYSIOLOGY 2005年第2期138卷 573-577页

作者： Girke, T Cheng, LC Raikhel, N Univ Calif Riverside Ctr Plant Cell Biol Dept Bot & Plant Sci Riverside CA 92521 USA

Chemical genomics is a promising new technology for studying gene functionsin the context of living organisms or cell systems. It complements existing molecular and geneticstools by allowing fine-tunable in vivo modulations of protein functions and cellular processes. Thispaper describes ChemMine, a chemoinformatics database that provides new online tools (***, descriptor generation) and integrates them with a wide variety of bioactive, natural andscreening compounds from public and commercial providers. Recent achievements in the use ofChemMine are discussed and future prospects are identified..

关键词： bioinformatics databases

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A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND bioinformatics 2012年第6期9卷 1850-1852页

作者： Campello, Ricardo J. G. B. Moulavi, Davoud Sander, Joerg Univ Alberta Dept Comp Sci Edmonton AB T6G 2E8 Canada Univ Sao Paulo Dept Comp Sci Sao Carlos SP Brazil

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

关键词： Data mining clustering bioinformatics databases AUTO-HDS

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Where do molecular biology graduate students find information?

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SCIENCE & TECHNOLOGY LIBRARIES 2005年第3期25卷 89-104页

作者： Brown, C Univ Oklahoma Sch Lib & Informat Studies Norman OK 73019 USA

Molecular biology graduate students read the traditional, highly regarded scientific journals, yet do not fully utilize bibliographic databases to find information. Instead, molecular biology graduate students rely on the extensive reservoir of information in bioinformatics databases as well as that within the National Library of Medicine's PubMed. Graduate students learn about bioinformatics databases in their laboratories, not the campus library, thereby bypassing the library and adopting the laboratory as their information community. The data presented suggest that science and technology librarians must expand their knowledge base to include these resources as well as provide instruction that is both palatable and transparent to the next generation of leaders in the field of molecular biology.

关键词： information seeking bioinformatics databases digital information scientific communication information community

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In silico identification of novel lncRNAs with a potential role in diagnosis of gastric cancer

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JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS 2020年第7期38卷 1954-1962页

作者： Delshad, Encieh Shamsabadi, Fatemeh T. Bahramian, Shabbou Mehravar, Fatemeh Maghsoudi, Hossein Shafiee, Mohammad Golestan Univ Med Sci Golestan Res Ctr Gastroenterol & Hepatol Gorgan Golestan Iran Golestan Univ Med Sci Fac Adv Technol Med Dept Med Biotechnol Gorgan Golestan Iran Golestan Univ Med Sci Hlth Management & Social Dev Res Ctr Gorgan Golestan Iran Payame Noor Univ Dept Biotechnol Tehran Iran

Gastric cancer (GC) is the second leading cause of cancer-related deaths in the world. Due to the shortage of adequate symptoms in the early stages, it is diagnosed when the tumor has spread to distant organs. Early recognition of GC enhances the chance of successful treatment. Molecular mechanisms of GC are still poorly understood. LncRNAs are emerging as new players in cancer in both oncogene and tumor suppressor roles. High-throughput technologies such as RNA-Seq, have revealed thousands of lncRNAs which are dysregulated in GC. In this study, we retrieved lncRNAs obtained by High-throughput technologies from OncoLnc database. Consequently, retrieved lncRNAs were compared in literature-based databases including PubMed. As a result, two lists, including experimentally validated lncRNAs and predicted lncRNAs were provided. We found 43 predicted lncRNAs that had not been experimentally validated in GC, so far. Further bioinformatics analyses were performed to obtain the expression profile of predicted lncRNAs in tumor and normal tissues. Also, the roles and targets of predicted lncRNAs in GC were identified by related databases. Finally, using the GEPIA database was reviewed the significant relationship of predicted lncRNAs with the survival of GC patients. By recognizing the lncRNAs involved in initiation and progression of GC, they may be considered as potential biomarkers in the GC early diagnosis or targeted treatment and lead to novel therapeutic strategies. Communicated by Ramaswamy H. Sarma

关键词： Gastric cancer predicted lncRNAs in silico analysis bioinformatics databases high-throughput technology

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An overview of long noncoding RNAs: Biology, functions, therapeutics, analysis methods, and bioinformatics tools

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CELL BIOCHEMISTRY AND FUNCTION 2022年第8期40卷 800-825页

作者： Jafari-Raddani, Farideh Davoodi-Moghaddam, Zeinab Yousefi, Amir-Mohammad Ghaffari, Seyed H. Bashash, Davood Shahid Beheshti Univ Med Sci Sch Allied Med Sci Dept Hematol & Blood Banking Tehran Iran Univ Tehran Med Sci Shariati Hosp Hematol Oncol & Stem Cell Transplantat Res Ctr Sch Med Tehran Iran

Long noncoding RNAs (lncRNAs) are a diverse class of RNAs whose functions are widespread in all branches of life and have been the focus of attention in the last decade. While a huge number of lncRNAs have been identified, there is still much work to be done and plenty to be learned. In the current review, we begin with the biogenesis and function of lncRNAs as they are involved in the different cellular processes from regulating the architecture of chromosomes to controlling translation and post-translation modifications. Questions on how overexpression, mutations, or deficiency of lncRNAs can affect the cellular status and result in the pathogenesis of various human diseases are responded to. Besides, we allocate an overview of several studies, concerning the application of lncRNAs either as diagnostic and prognostic biomarkers or novel therapeutics. We also introduce the currently available techniques to explore details of lncRNAs such as their function, cellular localization, and structure. In the last section, as exponentially growing data in this area need to be gathered and organized in comprehensive databases, we have a particular focus on presenting general and specialized databases. Taken together, with this review, we aim to provide the latest information on different aspects of lncRNAs to highlight their importance in physiopathologic states and take a step towards helping future studies.

关键词： bioinformatics databases epigenetic gene expression long noncoding RNA therapeutics

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Importance of Different Types of Prior Knowledge in Selecting Genome-Wide Findings for Follow-Up

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GENETIC EPIDEMIOLOGY 2013年第2期37卷 205-213页

作者： Minelli, Cosetta De Grandi, Alessandro Weichenberger, Christian X. Goegele, Martin Modenese, Mirko Attia, John Barrett, Jennifer H. Boehnke, Michael Borsani, Giuseppe Casari, Giorgio Fox, Caroline S. Freina, Thomas Hicks, Andrew A. Marroni, Fabio Parmigiani, Giovanni Pastore, Andrea Pattaro, Cristian Pfeufer, Arne Ruggeri, Fabrizio Schwienbacher, Christine Taliun, Daniel Pramstaller, Peter P. Domingues, Francisco S. Thompson, John R. European Acad Bozen Bolzano EURAC Ctr Biomed Bolzano Italy Univ Newcastle Hunter Med Res Inst Ctr Clin Epidemiol & Biostatist Newcastle NSW 2300 Australia John Hunter Hosp Dept Gen Med Newcastle NSW Australia Univ Leeds Sect Epidemiol & Biostat Leeds Inst Mol Med Leeds W Yorkshire England Univ Michigan Dept Biostat Ann Arbor MI 48109 USA Univ Michigan Ctr Stat Genet Ann Arbor MI 48109 USA Univ Brescia Dept Biomed Sci & Biotechnol Brescia Italy Univ Vita Salute San Raffaele Milan Italy Ctr Translat Genom & Bioinformat Milan Italy NHLBI Framingham Heart Study Framingham MA USA Ctr Populat Studies Framingham MA USA Inst Appl Genom Udine Italy Dana Farber Canc Inst Dept Biostat & Computat Biol Boston MA 02115 USA Harvard Univ Sch Publ Hlth Dept Biostat Boston MA 02115 USA Ca Foscari Venezia Univ Dept Econ Venice Italy German Res Ctr Environm Hlth GmbH Helmholtz Zentrum Munich Dept Bioinformat & Syst Biol IBIS Neuherberg Germany Inst Appl Math & Informat Technol Natl Res Council Milan Italy Cent Hosp Dept Neurol Bolzano Italy Med Univ Lubeck Dept Neurol D-23538 Lubeck Germany Univ Leicester Dept Hlth Sci Leicester Leics England

Biological plausibility and other prior information could help select genome-wide association (GWA) findings for further follow-up, but there is no consensus on which types of knowledge should be considered or how to weight them. We used experts opinions and empirical evidence to estimate the relative importance of 15 types of information at the single-nucleotide polymorphism (SNP) and gene levels. Opinions were elicited from 10 experts using a two-round Delphi survey. Empirical evidence was obtained by comparing the frequency of each type of characteristic in SNPs established as being associated with seven disease traits through GWA meta-analysis and independent replication, with the corresponding frequency in a randomly selected set of SNPs. SNP and gene characteristics were retrieved using a specially developed bioinformatics tool. Both the expert and the empirical evidence rated previous association in a meta-analysis or more than one study as conferring the highest relative probability of true association, whereas previous association in a single study ranked much lower. High relative probabilities were also observed for location in a functional protein domain, although location in a region evolutionarily conserved in vertebrates was ranked high by the data but not by the experts. Our empirical evidence did not support the importance attributed by the experts to whether the gene encodes a protein in a pathway or shows interactions relevant to the trait. Our findings provide insight into the selection and weighting of different types of knowledge in SNP or gene prioritization, and point to areas requiring further research.

关键词： gene prioritization genome-wide association studies bioinformatics databases

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Inferring Functional Groups from Microbial Gene Catalogue with Probabilistic Topic Models

Inferring Functional Groups from Microbial Gene Catalogue wi...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Chen, Xin He, TingTing Hu, Xiaohua An, Yuan Wu, Xindong Drexel Univ Coll Informat Sci & Technol Philadelphia PA 19104 USA Cent China Normal Univ Dept Comp Sci Wuhan Hubei Peoples R China Univ Vermont Dept Comp Sci Burlington VT USA

ISBN: (纸本)9780769545745

In this paper, based on the functional elements derived from non-redundant CDs catalogue, we show that the configuration of functional groups in meta-genome samples can be inferred by probabilistic topic modeling. The probabilistic topic modeling is a Bayesian method that is able to extract useful topical information from unlabeled data. When used to study microbial samples (assuming that relative abundance of functional elements is already obtained by a homology-based approach), each sample can be considered as a 'document', which has a mixture of functional groups, while each functional group (also known as a 'latent topic') is a weight mixture of functional elements (including taxonomic levels, and indicators of gene orthologous groups and KEGG pathway mappings). The functional elements bear an analogy with 'words'. Estimating the probabilistic topic model can uncover the configuration of functional groups (the latent topic) in each sample. The experimental results demonstrate the effectiveness of our proposed method.

关键词： Biological data mining Metagenomics Probabilistic topic model bioinformatics databases

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bioinformatics advances for clinical biomarker development

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Expert Opinion on Medical Diagnostics 2012年第1期6卷 39-48页

作者： Pritzker, Kenneth P.H. Pritzker, Laura B. Laboratory Medicine and Pathobiology Surgery University of Toronto Mount Sinai Hospital Toronto ON M5G 1X5 600 University Avenue Canada Rna Diagnostics Inc. Toronto ON M5G 2C2 595 Bay Street Canada

bioinformatics tools, techniques and resources are critical to biomarker discovery, assessment, validation, qualification, standardization and market acceptance into clinical practice. Huge scientific effort and economic investment over the past 20 years have resulted in thousands of new candidate biomarkers for diseases, yet relatively few biomarkers have entered clinical practice. bioinformatics is central to all stages of biomarker development and implementation. Areas covered: This review examines bioinformatics advances that bear on each stage of biomarker development and suggests bioinformatics strategies to assist biomarkers towards clinical practice. This paper focuses on the steps of clinical biomarker development with an emphasis on the review literature from 2000 to June 2011. The intent of this paper is to describe the present role of bioinformatics in biomarker development including the controversies associated with various developmental stages. Expert opinion: The key message is that more effective biomarker development requires database input of higher quality, improved bioinformatics tools to identify more clearly the acceptable criteria for each development step, as well as more and better database linkages. © 2012 Informa UK, Ltd.

关键词： bioinformatics bioinformatics databases biomarker biomarker qualification biomarker validation clinical utility comparative effectiveness predictive biomarker prognostic biomarker specimen repository

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Natural logic knowledge bases and their graph form

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DATA & KNOWLEDGE ENGINEERING 2020年 129卷 101848-101848页

作者： Andreasen, Troels Bulskov, Henrik Jensen, Per Anker Nilsson, Jurgen Fischer Roskilde Univ Comp Sci Roskilde Denmark Copenhagen Business Sch Management Soc & Commun Copenhagen Denmark Tech Univ Denmark Math & Comp Sci Lyngby Denmark

This paper describes how knowledge bases can be represented in and reasoned with in natural logic. Natural logic is a regimented fragment of natural language possessing a well-defined logical semantics. As such, natural logic may be considered an attractive alternative among the various knowledge representation logics such as description logics. Our version of natural logic expands formal ontologies with affirmative propositions expressing a variety of relationships between concepts. It comprises (nested) restrictive relative clauses and prepositional phrases and, as a new construct, adverbial prepositional phrases. The natural logic knowledge base is to be used for deductive query answering applying inference rules. This is facilitated by introduction of DATALOG as an embedding meta-logic. The inference rules are stated in DATALOG and act directly on the natural logic formulations. The knowledge base propositions are decomposed into a graph form enabling path finding between concepts. The examples in the paper are derived from text source life-science descriptions.

关键词： Natural Logic Knowledge management applications Ontologies Query Metalogic bioinformatics databases

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