34 research outputs found
Supplementary Data for NIPS Publication: Protein Interface Prediction using Graph Convolutional Networks.
No full text<p>These data sets can be used to re-run the experiments from our paper, Protein Interface Prediction using Graph Convolutional Networks. The data are derived from protein complexes in the docking benchmark dataset v. 5.0. Each file is a python tuple that has been saved using cPickle and compressed using gzip.</p>
<p>Links:</p>
<p>Paper: https://papers.nips.cc/paper/7231-protein-interface-prediction-using-graph-convolutional-networks</p>
<p>Poster: https://zenodo.org/record/1134154</p>
<p>Code: https://github.com/fouticus/pipgcn</p>
<p> </p>
<p><strong>File Descriptions:</strong></p>
<p>train.cpkl.gz and test.cpkl.gz have the data formatted for neighborhood based graph convolutions. The diffc_ files are the same data formatted for the diffusion convolutional neural networks that we compare against. </p>
<p>train.cpkl.gz is a tuple of length 2:</p>
<ul>
<li>element 0 is a list of length 175 containing the PDB codes from the docking benchmark dataset</li>
<li>element 1 is a list of length 175 containing features for each protein. Each element is a dictionary containing the following keys:
<ul>
<li>r_vertex: vertex (residue) features for the receptor. numpy array of shape (x, 70) where x is the number of residues in the receptor and 70 is the number of features.</li>
<li>l_vertex: vertex (residue) features for the ligand. analogous to above, with shape (y, 70) where y is the number of residues in the ligand.</li>
<li>complex_code: PDB code of the complex. matches the list of codes described above.</li>
<li>l_edge: edge features for the neighborhood around each residue in the ligand. numpy array of shape (y, 20, 2) where y is defined as above. the second dimension is the edges to the 20 nearest neighboring residues, ordered by decreasing distance. The third dimension allows for two features per edge. </li>
<li>r_edge: edge features for the neighborhood around each residue in the receptor. numpy array of shape (x, 20, 2) where x is as above. </li>
<li>l_hood_indices: the index of the 20 closest residues to each residue, ordered by decreasing distance. numpy array of shape (y, 20, 1). "Index" means which row in l_vertex gives the vertex features for the closest neighbor, second closest neighbor, etc. </li>
<li>r_hood_indices: analogous to above, shape (x, 20, 1).</li>
<li>label: 1 or -1 label for each residue pair. numpy array of shape (x*y, 3). Each row looks like (i, j, k) where i is the index of the ligand residue, j is the index of the receptor residue, and k is either -1 (negative example) or 1 (positive example).</li>
</ul>
</li>
</ul>
<p>test.cpkl.gz matches the structure of train.cpkl.gz except it has the test set of 55 complexes. </p>
<p>Descriptions of the vertex and edge features can be found in Appendix A of <a href="https://mountainscholar.org/handle/10217/185661">this.</a></p>
<p>diffc_g2_p2_train.cpkl.gz is a tuple of length 2:</p>
<ul>
<li>element 0 is a list of the same 175 PDB codes as above. </li>
<li>element 1 is a list of features for the 175 complexes. Each element is a dictionary of features with these keys:
<ul>
<li>r_vertex, l_vertex, complex_code, label: these are the same as described above. </li>
<li>'r_power_series': Stacked diffusion matrices which are powers of the similarity matrix used in the DCNN method. numpy array of shape (x, 2, x) where x is the number of receptor residues. the middle dimension 2 indicates how many "hops" is used for that diffusion (1 vs. 2). In other words, element (i, 0, j) is the similarity after 1 hops between residues i and j. element (i, 1, j) is the similarity after 2 hops. See DCNN paper for details.</li>
<li>'l_power_series': same as above but for the ligand. shape is (y, 2, y).</li>
</ul>
</li>
</ul>
<p>diffc_g2_p2_test.cpkl.gz is the same as diffc_g2_p2_train.cpkl.gz but for the 55 test complexes.</p>
<p>diff_g2_p5_train.cpkl.gz and diff_g2_p5_test.cpkl.gz are the same as the p2 version above, except that the diffusion matrices have shape (x, 5, x) and (y, 5, y) because one of our comparisons against the DCNN model uses 5 hops instead of just 2. </p>
<p> </p>
<p>Note: these files were pickled with Python 2.7. If you're unpickling with Python 3.x you might have to specify encoding as 'latin1'. </p>
<p> </p>
<p>Please direct any questions to:</p>
<ul>
<li>Alex Fout ([email protected])</li>
<li>Jonathon Byrd ([email protected])</li>
<li>Basir Shariat ([email protected]</li>
<li>Asa Ben-Hur ([email protected])</li>
</ul>This work was supported by the National Science Foundation under grant no DBI-156484
105 - Alex M Fout
No full textIncludes bibliographical references.This poster was presented at the 2017 Colorado State University Graduate Student Showcase, 9 November 2017.Determining the interface between two interacting proteins can help illuminate cellular biology, improve our understanding of disease, and aid pharmaceutical research. Such determination is expensive and time consuming using wet-lab experiments, which has motivated the development of computational methods. Inspired by the success of deep learning in image processing and other application areas, we adapt convolutional neural networks to work with irregularly structured data, such as proteins. We construct a novel pairwise classification architecture which is trained and tested with data from the Docking Benchmark Dataset versions 4.0 and 5.0. This outperforms the existing state-of-the-art prediction method, PAIRpred.Graduate Student Council - New Graduate Student - Research Top Scholar
A Critique of the Correction of Nizamiâs Khamseh by Basir Mozhdehi Compared with Corrections of Vahid Dastgerdi and Moscow
No full textUntil now we have been familiar with several corrections of Nizamiâs Khamseh like Vahid Dastgerdi, Moscow, Servatian and Barat Zanjani but in recent years a new correction has been published by Samieh Basir Mozhdehi (reviewed by Baha al-Din Khoramshahi) whose first and second imprints were published by Dustan publishing in 1383 and 1388 respectively. Such correction has been done based on the so-called version of Saâdloo (due to the fact that this version has been found in a family with the very name) which belongs to eight century (A.H) and via contrasting with versions of central library of Tehran University, Vahid Dastgerdi and Russian Academy of Science. The author thinks that her findings and understandings of the verses, using the most correct variants (in her view), considering the rules of rhyme, styles of poetry, prosody and other rhetorical techniques, and using the version of Saâdloo as the basis of her correction have altogether made her correction more authentic and closer to the main version of Nizamiâs work.
It should be mentioned that although this correction is recent and could apply the results of new sciences besides having access to two authentic versions of Vahid and Moscow to provide a better work than the predecessorsâ, it is unfortunately one of the corrections with most mistakes and problems. While indicating to some verses in this correction and comparing it with the versions of Vahid and Moscow (that the corrector has acknowledged her correction has been contrasted particularly with these two ones), this research aims to show that such correction is not authentic. The important point is that, contrary to the words of author about paying attention to poetic styles and techniques, the reader finds out after close reading that unfortunately the corrector lacks sufficient knowledge about such rules and even the morphology and poetic space of Nizami
Summary of research results, management recommendations and farmer workshops from cacao agroforestry landscapes in Indonesia
No full textSoftcover, 17,6x25Cacao agroforestry systems are common in Indonesia, but differences in local management affect
biodiversity and related ecosystem services. Importantly, birds and bats alike strongly contribute
to biological pest control in cacao, thereby promoting yields and sustainable farming. Our findings
from many years of ecological field research, in close collaboration with Indonesian cacao farmers,
are summarized and discussed in this bilingual book, written in both English and Indonesian. It is
designed to communicate scientific information as well as to facilitate transdisciplinary discussions
and more biodiversity-friendly management in tropical agroforestry systems.
We consider this book as a tool to improve the collaboration of local communities, farmers and
scientists, as well as to improve the application of scientific knowledge in agricultural practice -
particularly in tropical land use areas.
Bea Maas, the first author of this book, is postdoctoral researcher at the University of Vienna
(Austria), working in the fields of biology, ecology and conservation. She conducted the research and
workshops presented here in close collaboration and with support from the University of Göttingen
(Germany) and the University of Tadulako (Indonesia).Sistem agroforestri kakao adalah hal umum di Indonesia, tetapi perbedaan pengelolaan setempat
akan mempengaruhi keanekaragaman hayati dan layanan ekosistem. Terutama, burung dan kelelawar
sama-sama memberikan kontribusi tinggi pada pengendalian hama biologis di kakao, sehingga
dapat meningkatkan hasil panen dan pertanian yang berkelanjutan. Temuan kami dari penelitian
lapangan ekologi bertahun-tahun, yang bekerjasama erat dengan petani kakao Indonesia, dirangkum
dan dibahas dalam buku bilingual ini, tertulis dalam bahasa Inggris dan bahasa Indonesia. Buku
ini dirancang untuk mengkomunikasikan informasi ilmiah dan juga untuk memfasilitasi diskusi
transdisipliner dan pengelolaan keanekaragaman hayati yang ramah pada sistem agroforestri tropis.
Kami menganggap buku ini sebagai alat untuk meningkatkan kolaborasi masyarakat lokal, petani
dan ilmuwan, serta untuk meningkatkan penerapan pengetahuan ilmiah dalam praktik pertanian -
terutama di wilayah penggunaan lahan tropis.
Bea Maas, penulis pertama buku ini, adalah peneliti postdoctoral di Universitas Wina (Austria),
bekerja di bidang biologi, ekologi dan konservasi. Dia melakukan penelitian dan lokakarya yang
disampaikan dalam buku ini dengan kerjasama yang erat dan dukungan dari Universitas Göttingen
(Jerman) dan Universitas Tadulako (Indonesia)
Social capital and inequality in immigrant entrepreneurship: pathways and barriers
No full textImmigrant entrepreneurs who belong to marginalized populations face significant financial, social, cultural, and legal barriers (Hernandez, 2024). While founding and sustaining a new business is not an equal experience for all (Guzman & Kacperczyk, 2019), entrepreneurship offers marginalized people a pathway to greater economic inclusion and social mobility (Min & Bozorgmehr, 2003; Hwang & Phillips, 2023; Rider et al., 2023). Furthermore, despite the risks associated with new enterprises, immigrants are more likely than their native-born counterparts to become entrepreneurs (Kerr & Kerr, 2020). Considering this evidence, entrepreneurship has the potential to offer marginalized immigrants a pathway to economic inclusion and social mobility. As organizational scholars and members of an unequal society with growing anti-immigrant sentiment, it is crucial to investigate the mechanisms that could reduce barriers to entrepreneurial entry and growth for marginalized immigrants. The literature on social capital identifies it as a powerful resource facilitating entrepreneurial success (Burt, 1992; Lin et al., 2001; Adler and Kwon, 2002; Samila & Sorenson, 2017; Portes & Sensenbrenner, 1993). However, in the context of immigrant entrepreneurship, the role of social capital is far from straightforward.. Immigrants, being foreign to the host country, often lack access to the social networks that facilitate entrepreneurial entry, especially in the absence of resource-rich ethnic enclaves (Portes & Stepick, 1985). Even when such networks exist, cultural norms or an overreliance on insular perspectives within these enclaves can limit entrepreneurial ambition and growth (Portes, 2014). Finally, first-order barriers such as marginalized identities may further constrain immigrants’ ability to cultivate resourceful social ties. This symposium tackles such intricacies in the literature to advance our understanding of social capital and inequality in the context of immigrant entrepreneurship. It will feature research that explores how social capital shapes inequities in immigrant entrepreneurship and examines interventions to mitigate these disparities. Key questions addressed include: a) Can social capital offset financial inequities that hinder entrepreneurial entry? b) How do multiple overlapping identities of people influence their engagement with entrepreneurial ecosystems and networks? c) What interventions, such as macro policy changes or digital tools, can reduce the social network-driven inequities faced by immigrant entrepreneurs? The Impact of Financial Constraints on Entrepreneurship: The Moderating Role Of Social Capital Author: Inara Tareque; Columbia Business School Navigating Identity Networks in Entrepreneurial Ecosystems Author: Nada Basir; University of Waterloo Author: Bessma Momani; University of Waterloo Author: Melissa Finn; University of Waterloo Author: Leslie Nichols; Wilfrid Laurier University The Entrepreneurial Dynamics of Trade Liberalization: Immigrants as Agents of Change Author: Ashlee Li; Author: Astrid Marinoni; Georgia Institute of Technology A Digital Refuge: How WhatsApp Offers Stability Amidst Mobility to NYC Asylum Seekers Author: Sandra Portocarrero; The London School of Economics & Political Science Author: Rohini Jalan; McGill Universit
Analysis of health in health centers area in Depok using correspondence analysis and scan statistic
No full textMythological Intertextuality in “Harry Potter and The Cursed Child” Special Rehearsal Edition
No full textThis thesis focused on the mythological intertextuality in “Harry Potter and The
Cursed Child” special rehearsal edition (2016). There are two objectives of the research
in this thesis, they are (1) to find out the mythologies intertexted in the novel and (2)
to see how those mythologies involved in the construction of the story to help building
it up.
This research used descriptive qualitative method since the main data’s source is
from the texts of the novel by J.K Rowling. In collecting the data, the researcher relied
on himself as the main instrument that collected them and then analysed them using
the basic concept of the theory of intertextuality by Julia Kristeva combined with the
common general definition of mythology forming mythological intertextuality.
The result of the research revealed that there are 18 mythologies that inserted by
the author into the novel which can be categorized: 4 objects, 5 characters, and 9
creatures.
Those mythologies involved in the construction of the story, which are theme,
characters, plot and setting. Most of the mythologies inserted by the author involved in
the character element since it covers up the mythological figures and creatures. It can
be seen that the author brought the mythologies combined with her creativity or another
external elements in arranging the story because the mythologies do not dominated the
element yet they have their participation in constructing it
Universalitas Dalam Karya Sastra: Aspek Representasional, Diskursif, Dan Nilai Filsafat Novel The Alchemist Karya Paulo Coelho
No full text"The Alchemist" composition of Paulo Coelho is a novel of world class (winner nobel) that is translated from Spain (0 Alquimista) to various languages, including English and Indonesian. The translation of Indonesian, carried out by Tanti Lesmana (publisher Gramedia), has been considered good enough and used as items of lecturing of art in various college. Its content is wide enough. Besides depicting real fact live with creative touch of his author, it is loaded with various social messages which are so meaningful. At least, there are three important aspects drawn uppermostly in the novel: aspect of representational, diskursif, and philosophy. The author presents various facts of life and historical-geographical reality (aspect representational). For movement of especial figure and develop; build story so that draw used by various strategy, for example occult signal, third person help, and the symbolism (aspect diskursif). And most important is presenting of various human drama which can be taken by its benefit of both for positive and or the negativity (philosophy aspect).</jats:p
