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                        "title": "SignalP 4.0: Discriminating signal peptides from transmembrane regions",
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                                "name": "Petersen T.N."
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                        "title": "Uncovering the molecular machinery of the human spindle-an integration of wet and dry systems biology",
                        "abstract": "The mitotic spindle is an essential molecular machine involved in cell division, whose composition has been studied extensively by detailed cellular biology, high-throughput proteomics, and RNA interference experiments. However, because of its dynamic organization and complex regulation it is difficult to obtain a complete description of its molecular composition. We have implemented an integrated computational approach to characterize novel human spindle components and have analysed in detail the individual candidates predicted to be spindle proteins, as well as the network of predicted relations connecting known and putative spindle proteins. The subsequent experimental validation of a number of predicted novel proteins confirmed not only their association with the spindle apparatus but also their role in mitosis. We found that 75% of our tested proteins are localizing to the spindle apparatus compared to a success rate of 35% when expert knowledge alone was used. We compare our results to the previously published MitoCheck study and see that our approach does validate some findings by this consortium. Further, we predict so-called \"hidden spindle hub\", proteins whose network of interactions is still poorly characterised by experimental means and which are thought to influence the functionality of the mitotic spindle on a large scale. Our analyses suggest that we are still far from knowing the complete repertoire of functionally important components of the human spindle network. Combining integrated bio-computational approaches and single gene experimental follow-ups could be key to exploring the still hidden regions of the human spindle system. © 2012 Rojas et al.",
                        "date": "2012-03-09T00:00:00Z",
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                        "authors": [
                            {
                                "name": "Rojas A.M."
                            },
                            {
                                "name": "Santamaria A."
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                            {
                                "name": "Malik R."
                            },
                            {
                                "name": "Jensen T.S."
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                            {
                                "name": "Korner R."
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                            {
                                "name": "Morilla I."
                            },
                            {
                                "name": "de Juan D."
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                            {
                                "name": "Krallinger M."
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                            {
                                "name": "Hansen D.A."
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                            {
                                "name": "Hoffmann R."
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                            {
                                "name": "Lees J."
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                            {
                                "name": "Reid A."
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                            {
                                "name": "Yeats C."
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                            {
                                "name": "Wehner A."
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                            {
                                "name": "Elowe S."
                            },
                            {
                                "name": "Clegg A.B."
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                            {
                                "name": "Brunak S."
                            },
                            {
                                "name": "Nigg E.A."
                            },
                            {
                                "name": "Orengo C."
                            },
                            {
                                "name": "Valencia A."
                            },
                            {
                                "name": "Ranea J.A.G."
                            }
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                        "journal": "PLoS ONE"
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        },
        {
            "name": "NCBI Mass Sequence Downloader",
            "description": "This program will download sequences en masse from several NCBI databases (at the user's choice). After the downloading is finished, the program will check the resulting file for any missing sequences and continuously retry the download until all sequences are present in the local file. NCBI Data Usage Policies and Disclaimers may apply to downloaded data.",
            "homepage": "https://github.com/StuntsPT/NCBI_Mass_Downloader",
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                {
                    "operation": [
                        {
                            "uri": "http://edamontology.org/operation_2422",
                            "term": "Data retrieval"
                        }
                    ],
                    "input": [],
                    "output": [
                        {
                            "data": {
                                "uri": "http://edamontology.org/data_0850",
                                "term": "Sequence set"
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                    "term": "Computational biology"
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            ],
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                "Python"
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                    "url": "https://github.com/StuntsPT/NCBI_Mass_Downloader/releases",
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                {
                    "url": "https://github.com/StuntsPT/NCBI_Mass_Downloader/releases",
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                    "url": "http://ncbi-mass-sequence-downloader.readthedocs.io/en/latest/",
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            "publication": [
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                    "doi": "10.1016/j.softx.2016.04.007",
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                    "metadata": {
                        "title": "NCBI Mass Sequence Downloader–Large dataset downloading made easy",
                        "abstract": "© 2016 The Author(s)Sequence databases, such as NCBI, are a very important resource in many areas of science. Downloading small amounts of sequences to local storage can easily be performed using any recent web browser, but downloading tens of thousands of sequences is not as simple. NCBI Mass Sequence Downloader is an open source program aimed at simplifying obtaining large amounts of sequence data from NCBI databases to local storage. It is written in python (can be run under both python 2 and python 3), and uses PyQt5 for the GUI. The program can be run in either graphical or command line mode. Source code is licensed under the GPLv3, and is supported on Linux, Windows and Mac OSX. Available at https://github.com/ElsevierSoftwareX/SOFTX-D-15-00072.git, https://github.com/StuntsPT/NCBI_Mass_Downloader",
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                                "name": "Pina-Martins F."
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