BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology.

BindingDB, www.bindingdb.org, is a publicly accessible database of experimental protein-small molecule interaction data. Its collection of over a million data entries derives primarily from scientific articles and, increasingly, US patents. BindingDB provides many ways to browse and search for data of interest, including an advanced search tool, which can cross searches of multiple query types, including text, chemical structure, protein sequence and numerical affinities. The PDB and PubMed provide links to data in BindingDB, and vice versa; and BindingDB provides links to pathway information, the ZINC catalog of available compounds, and other resources. The BindingDB website offers specialized tools that take advantage of its large data collection, including ones to generate hypotheses for the protein targets bound by a bioactive compound, and for the compounds bound by a new protein of known sequence; and virtual compound screening by maximal chemical similarity, binary kernel discrimination, and support vector machine methods. Specialized data sets are also available, such as binding data for hundreds of congeneric series of ligands, drawn from BindingDB and organized for use in validating drug design methods. BindingDB offers several forms of programmatic access, and comes with extensive background material and documentation. Here, we provide the first update of BindingDB since 2007, focusing on new and unique features and highlighting directions of importance to the field as a whole

The driving force of government in promoting BIM implementation

The adoption of Building Information Modelling (BIM) is one of the greatest technological innovations in the construction industry to date. However, the implementation of BIM lags far behind its potential due to the existence of various barriers. Strong government support is critical for the successful development and deployment of complex technology systems. BIM could seek government support to drive its implementation process and overcome the barriers. Through a survey, this paper aims to discover stakeholders’ expectations of the government role in BIM implementation and explores specific ways for governments to promote BIM implementation. The research findings are expected to assist related departments to accelerate BIM implementation

Challenges of Being a Chinese Principal: Practitioner Perspectives

This qualitative study examined how public-school principals spent their professional day, the challenges they faced, and their advice to new principals regarding how to respond to the challenges they identified. The themes that emerged from the data underscored the demands of high-stakes test preparation that the participants felt undermined education quality and stifled student creativity. The relationships across themes that emerged identified being a good teacher and life-long learner as essential to instructional supervision and maintaining one’s focus on raising the quality of student’s educational experiences. Demonstrating a good moral character was even more critical, however, to maintaining one’s priorities and serving as a role model for teachers and students

Contextual Language Model Adaptation for Conversational Agents

Statistical language models (LM) play a key role in Automatic Speech Recognition (ASR) systems used by conversational agents. These ASR systems should provide a high accuracy under a variety of speaking styles, domains, vocabulary and argots. In this paper, we present a DNN-based method to adapt the LM to each user-agent interaction based on generalized contextual information, by predicting an optimal, context-dependent set of LM interpolation weights. We show that this framework for contextual adaptation provides accuracy improvements under different possible mixture LM partitions that are relevant for both (1) Goal-oriented conversational agents where it's natural to partition the data by the requested application and for (2) Non-goal oriented conversational agents where the data can be partitioned using topic labels that come from predictions of a topic classifier. We obtain a relative WER improvement of 3% with a 1-pass decoding strategy and 6% in a 2-pass decoding framework, over an unadapted model. We also show up to a 15% relative improvement in recognizing named entities which is of significant value for conversational ASR systems.Comment: Interspeech 2018 (accepted

Essential gene pathways for glioblastoma stem cells: clinical implications for prevention of tumor recurrence.

Glioblastoma (World Health Organization/WHO grade IV) is the most common and most aggressive adult glial tumor. Patients with glioblastoma, despite being treated with gross total resection and post-operative radiation/chemotherapy, will almost always develop tumor recurrence. Glioblastoma stem cells (GSC), a minor subpopulation within the tumor mass, have been recently characterized as tumor-initiating cells and hypothesized to be responsible for post-treatment recurrence because of their enhanced radio-/chemo-resistant phenotype and ability to reconstitute tumors in mouse brains. Genome-wide expression profile analysis uncovered molecular properties of GSC distinct from their differentiated, proliferative progeny that comprise the majority of the tumor mass. In contrast to the hyperproliferative and hyperangiogenic phenotype of glioblastoma tumors, GSC possess neuroectodermal properties and express genes associated with neural stem cells, radial glial cells, and neural crest cells, as well as portray a migratory, quiescent, and undifferentiated phenotype. Thus, cell cycle-targeted radio-chemotherapy, which aims to kill fast-growing tumor cells, may not completely eliminate glioblastoma tumors. To prevent tumor recurrence, a strategy targeting essential gene pathways of GSC must be identified and incorporated into the standard treatment regimen. Identifying intrinsic and extrinsic cues by which GSC maintain stemness properties and sustain both tumorigenesis and anti-apoptotic features may provide new insights into potentially curative strategies for treating brain cancers

A Timely Update of Global COVID-19 Vaccine Development

The International Society for Vaccines (ISV) launched a virtual congress series www.ISVCongress.org as the leading platform for key COVID‐19 vaccine developersto share their progress and for the global vaccine community to contribute their collective expertise and wisdom about broader aspects of the global pandemic vaccine response. The aims were threefold: 1) to provide timely information about the processes put in place by regulatory agencies and NGOs for COVID-19 vaccine development, 2) to present primary data from groups developing vaccines, and 3) to provide a forum for discussion by experts about key challenges that confront the COVID-19 vaccine development process