Search results for "biological data"
showing 10 items of 53 documents
New Trends in Graph Mining
2010
Searching for repeated features characterizing biological data is fundamental in computational biology. When biological networks are under analysis, the presence of repeated modules across the same network (or several distinct ones) is shown to be very relevant. Indeed, several studies prove that biological networks can be often understood in terms of coalitions of basic repeated building blocks, often referred to as network motifs.This work provides a review of the main techniques proposed for motif extraction from biological networks. In particular, main intrinsic difficulties related to the problem are pointed out, along with solutions proposed in the literature to overcome them. Open ch…
Data Sources and Models
2017
Biological networks rely on the storage and retrieval of data associated to the physical interactions and/or functional relationships among different actors. In particular, the attention may be on the interactions among cellular components, such as proteins, genes, RNA, or for example on phenotype–genotype associations. Data from which biological networks are built are usually stored in public databases, and we provide here a brief summary of the main types of both data and associations, publicly available. Moreover, we also explain how it is possible to construct suitable network models from these associations, focusing on protein–protein interaction networks, gene–disease networks and net…
Protein Interaction Networks and Disease: Highlights of the 3rd Challenges in Computational Biology Meeting
2017
Cellular functions are managed by a complex network of protein interactions, the malfunction of which may derive in disease phenotypes. In spite of the incompleteness and noise present in our current protein interaction maps, computational biologists are making strenuous efforts to extract knowledge from these intricate networks and, through their integration with other types of biological data, expedite the development of novel and more effective treatments against human disorders. The 3rd Challenges in Computational Biology meeting revolved around the Protein Interaction Networks and Disease subject, bringing expert network biologists to the city of Mainz, Germany to debate the current st…
Textual data compression in computational biology: Algorithmic techniques
2012
Abstract In a recent review [R. Giancarlo, D. Scaturro, F. Utro, Textual data compression in computational biology: a synopsis, Bioinformatics 25 (2009) 1575–1586] the first systematic organization and presentation of the impact of textual data compression for the analysis of biological data has been given. Its main focus was on a systematic presentation of the key areas of bioinformatics and computational biology where compression has been used together with a technical presentation of how well-known notions from information theory have been adapted to successfully work on biological data. Rather surprisingly, the use of data compression is pervasive in computational biology. Starting from…
A summary of genomic databases: overview and discussion
2009
In the last few years both the amount of electronically stored biological data and the number of biological data repositories grew up significantly (today, more than eight hundred can be counted thereof). In spite of the enormous amount of available resources, a user may be disoriented when he/she searches for specific data. Thus, the accurate analysis of biological data and repositories turn out to be useful to obtain a systematic view of biological database structures, tools and contents and, eventually, to facilitate the access and recovery of such data. In this chapter, we propose an analysis of genomic databases, which are databases of fundamental importance for the research in bioinfo…
BIOfid dataset: publishing a German gold standard for named entity recognition in historical biodiversity literature
2019
The Specialized Information Service Biodiversity Research (BIOfid) has been launched to mobilize valuable biological data from printed literature hidden in German libraries for over the past 250 years. In this project, we annotate German texts converted by OCR from historical scientific literature on the biodiversity of plants, birds, moths and butterflies. Our work enables the automatic extraction of biological information previously buried in the mass of papers and volumes. For this purpose, we generated training data for the tasks of Named Entity Recognition (NER) and Taxa Recognition (TR) in biological documents. We use this data to train a number of leading machine learning tools and c…
Quinoline-Based Molecules Targeting c-Met, EGF, and VEGF Receptors and the Proteins Involved in Related Carcinogenic Pathways
2020
The quinoline ring system has long been known as a versatile nucleus in the design and synthesis of biologically active compounds. Currently, more than one hundred quinoline compounds have been approved in therapy as antimicrobial, local anaesthetic, antipsychotic, and anticancer drugs. In drug discovery, indeed, over the last few years, an increase in the publication of papers and patents about quinoline derivatives possessing antiproliferative properties has been observed. This trend can be justified by the versatility and accessibility of the quinoline scaffold, from which new derivatives can be easily designed and synthesized. Within the numerous quinoline small molecules developed as a…
The Three Steps of Clustering In The Post-Genomic Era
2013
This chapter descibes the basic algorithmic components that are involved in clustering, with particular attention to classification of microarray data.
Compression-based classification of biological sequences and structures via the Universal Similarity Metric: experimental assessment.
2007
Abstract Background Similarity of sequences is a key mathematical notion for Classification and Phylogenetic studies in Biology. It is currently primarily handled using alignments. However, the alignment methods seem inadequate for post-genomic studies since they do not scale well with data set size and they seem to be confined only to genomic and proteomic sequences. Therefore, alignment-free similarity measures are actively pursued. Among those, USM (Universal Similarity Metric) has gained prominence. It is based on the deep theory of Kolmogorov Complexity and universality is its most novel striking feature. Since it can only be approximated via data compression, USM is a methodology rath…
PVAmpliconFinder: a workflow for the identification of human papillomaviruses from high-throughput amplicon sequencing
2019
Abstract Background The detection of known human papillomaviruses (PVs) from targeted wet-lab approaches has traditionally used PCR-based methods coupled with Sanger sequencing. With the introduction of next-generation sequencing (NGS), these approaches can be revisited to integrate the sequencing power of NGS. Although computational tools have been developed for metagenomic approaches to search for known or novel viruses in NGS data, no appropriate tool is available for the classification and identification of novel viral sequences from data produced by amplicon-based methods. Results We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify kno…