An integrative modular approach to systematically predict gene-phenotype associations

Autor: Waterman Michael S, Dai Chao, Nunez-Iglesias Juan, Mehan Michael R, Zhou Xianghong

Publikováno v: BMC Bioinformatics, Vol 11, Iss Suppl 1, p S62 (2010)

Abstract Background Complex human diseases are often caused by multiple mutations, each of which contributes only a minor effect to the disease phenotype. To study the basis for these complex phenotypes, we developed a network-based approach to ident

Externí odkaz: https://doaj.org/article/68f61c3931d7446fa73f81e0edc53486

Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach

Autor: Luan Yihui, Nunez-Iglesias Juan, Wang Wenhui, Sun Fengzhu

Publikováno v: BMC Bioinformatics, Vol 10, Iss 1, p 277 (2009)

Abstract Background Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn al

Externí odkaz: https://doaj.org/article/1544898e3b5946bc9d84416b6b4e8b1a

Synaptic Cleft Segmentation in Non-Isotropic Volume Electron Microscopy of the Complete Drosophila Brain

Autor: Heinrich, Larissa, Funke, Jan, Pape, Constantin, Nunez-Iglesias, Juan, Saalfeld, Stephan

Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron microscopy in serial transmission or scanning mode has been demonstra

Externí odkaz: http://arxiv.org/abs/1805.02718

The Astropy Problem

Autor: Muna, Demitri, Alexander, Michael, Allen, Alice, Ashley, Richard, Asmus, Daniel, Azzollini, Ruyman, Bannister, Michele, Beaton, Rachael, Benson, Andrew, Berriman, G. Bruce, Bilicki, Maciej, Boyce, Peter, Bridge, Joanna, Cami, Jan, Cangi, Eryn, Chen, Xian, Christiny, Nicholas, Clark, Christopher, Collins, Michelle, Comparat, Johan, Cook, Neil, Croton, Darren, Davids, Isak Delberth, Depagne, Éric, Donor, John, Santos, Leonardo A. dos, Douglas, Stephanie, Du, Alan, Durbin, Meredith, Erb, Dawn, Faes, Daniel, Fernández-Trincado, J. G., Foley, Anthony, Fotopoulou, Sotiria, Frimann, Søren, Frinchaboy, Peter, Garcia-Dias, Rafael, Gawryszczak, Artur, George, Elizabeth, Gonzalez, Sebastian, Gordon, Karl, Gorgone, Nicholas, Gosmeyer, Catherine, Grasha, Katie, Greenfield, Perry, Grellmann, Rebekka, Guillochon, James, Gurwell, Mark, Haas, Marcel, Hagen, Alex, Haggard, Daryl, Haines, Tim, Hall, Patrick, Hellwing, Wojciech, Herenz, Edmund Christian, Hinton, Samuel, Hlozek, Renee, Hoffman, John, Holman, Derek, Holwerda, Benne Willem, Horton, Anthony, Hummels, Cameron, Jacobs, Daniel, Jensen, Jens Juel, Jones, David, Karick, Arna, Kelley, Luke, Kenworthy, Matthew, Kitchener, Ben, Klaes, Dominik, Kohn, Saul, Konorski, Piotr, Krawczyk, Coleman, Kuehn, Kyler, Kuutma, Teet, Lam, Michael T., Lane, Richard, Liske, Jochen, Lopez-Camara, Diego, Mack, Katherine, Mangham, Sam, Mao, Qingqing, Marsh, David J. E., Mateu, Cecilia, Maurin, Loïc, McCormac, James, Momcheva, Ivelina, Monteiro, Hektor, Mueller, Michael, Munoz, Roberto, Naidu, Rohan, Nelson, Nicholas, Nitschelm, Christian, North, Chris, Nunez-Iglesias, Juan, Ogaz, Sara, Owen, Russell, Parejko, John, Patrício, Vera, Pepper, Joshua, Perrin, Marshall, Pickering, Timothy, Piscionere, Jennifer, Pogge, Richard, Poleski, Radek, Pourtsidou, Alkistis, Price-Whelan, Adrian M., Rawls, Meredith L., Read, Shaun, Rees, Glen, Rein, Hanno, Rice, Thomas, Riemer-Sørensen, Signe, Rusomarov, Naum, Sanchez, Sebastian F., Santander-García, Miguel, Sarid, Gal, Schoenell, William, Scholz, Aleks, Schuhmann, Robert L., Schuster, William, Scicluna, Peter, Seidel, Marja, Shao, Lijing, Sharma, Pranav, Shulevski, Aleksandar, Shupe, David, Sifón, Cristóbal, Simmons, Brooke, Sinha, Manodeep, Skillen, Ian, Soergel, Bjoern, Spriggs, Thomas, Srinivasan, Sundar, Stevens, Abigail, Streicher, Ole, Suchyta, Eric, Tan, Joshua, Telford, O. Grace, Thomas, Romain, Tonini, Chiara, Tremblay, Grant, Tuttle, Sarah, Urrutia, Tanya, Vaughan, Sam, Verdugo, Miguel, Wagner, Alexander, Walawender, Josh, Wetzel, Andrew, Willett, Kyle, Williams, Peter K. G., Yang, Guang, Zhu, Guangtun, Zonca, Andrea

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed,

Externí odkaz: http://arxiv.org/abs/1610.03159

Machine learning of hierarchical clustering to segment 2D and 3D images

Autor: Nunez-Iglesias, Juan, Kennedy, Ryan, Parag, Toufiq, Shi, Jianbo, Chklovskii, Dmitri B.

Publikováno v: PLoS ONE, 2013, 8(8): e71715

We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple feature

Externí odkaz: http://arxiv.org/abs/1303.6163