Private Sequential Learning

Can we learn privately and efficiently through sequential interactions? A private learning model is formulated to study an intrinsic tradeoff between privacy and query complexity in sequential learning. The formulation involves a learner who aims to learn a scalar value by sequentially querying an external database and receiving binary responses. In the meantime, an adversary observes the learner’s queries, although not the responses, and tries to infer from them the scalar value of interest. The objective of the learner is to obtain an accurate estimate of the scalar value using only a small number of queries while simultaneously protecting his or her privacy by making the scalar value provably difficult to learn for the adversary. The main results provide tight upper and lower bounds on the learner’s query complexity as a function of desired levels of privacy and estimation accuracy. The authors also construct explicit query strategies whose complexity is optimal up to an additive constant.

Metabolic networks of the Nicotiana genus in the spotlight: content, progress and outlook

Manually curated metabolic databases residing at the Sol Genomics Network comprise two taxon-specific databases for the Solanaceae family, i.e. SolanaCyc and the genus Nicotiana, i.e. NicotianaCyc as well as six species-specific databases for Nicotiana tabacum TN90, N. tabacum K326, Nicotiana benthamiana, N. sylvestris, N. tomentosiformis and N. attenuata. New pathways were created through the extraction, examination and verification of related data from the literature and the aid of external database guided by an expert-led curation process. Here we describe the curation progress that has been achieved in these databases since the first release version 1.0 in 2016, the curation flow and the curation process using the example metabolic pathway for cholesterol in plants. The current content of our databases comprises 266 pathways and 36 superpathways in SolanaCyc and 143 pathways plus 21 superpathways in NicotianaCyc, manually curated and validated specifically for the Solanaceae family and Nicotiana genus, respectively. The curated data have been propagated to the respective Nicotiana-specific databases, which resulted in the enrichment and more accurate presentation of their metabolic networks. The quality and coverage in those databases have been compared with related external databases and discussed in terms of literature support and metabolic content.

Real-world data validation for differential expression of immunoregulatory molecules and targetable cancer genes may provide therapeutic insights into agnostic-driven trial designs.

10 Background: Targeting actionable genes and using immunotherapy have increased treatment options. We previously reported that some immunoregulatory molecules are found differentially regulated in the presence of certain gene mutations regardless of cancer subtype. Here we validated a subset of these associations in an independent, real-world dataset with distinct clinicopathological characteristics. Methods: Previously, 2740 TCGA patients were identified to have at least one potentially oncogenic mutation (mt) within an established 50-gene hotspot panel. Differential expression of 10 immunoregulatory molecules (IRM) was analyzed between mutant (mt) vs. wild-type (wt). To ensure observed significant associations were not confounded by tumor-type, differential IRM expression within mt-enriched tumor-types was compared to that of mt vs. wt. Now, using the NantHealth external database of 2739 unselected clinical cases these associations were validated. Results: Within the TCGA cohort 19/50 gene mutations were found to be significantly associated with ≥1 IRM expression. In many, the mt effect-size was larger than that of tumor-type; e.g. head & neck carcinomas (HNSCC) are highly enriched for CDKN2A mt (OR = 4.9, p = 4.3e-9), yet CDKN2A mt are more associated with CTLA4 expression than HNSCC histology (t = 7.0 vs. 5.4). Of these 15 associations, 6 were validated within the independent later-stage NantHealth cohort. Most notably, CDKN2A mt was validated as associated with increased PD1 and CTLA4 expression while KRAS and APC mt were validated as associated with decreased PDL1/2 expression. Conclusions: The presented differential checkpoint expression patterns are strongly associated with mutation status and are not primarily driven by tissue-type, which have been further validated by an external database. Strategies combining genomic targets have been shown to yield success as well as using immunotherapies. Our data suggests there may be a role for combining NGS targets along with IRM expression patterns to better guide future design of clinical trials in combatting various cancers in a tissue-agnostic fashion.

TUGAS JARINGAN KOMPUTER 1 (YUDA FAHROZI 175100011)

Database Server adalah sebuah program komputer yang menyediakan layanan pengelolaan basis data dan melayani komputer atau program aplikasi basis data yang menggunakan model klien/server. Istilah ini juga merujuk kepada sebuah komputer (umumnya merupakan server) yang didedikasikan untuk menjalankan program yang bersangkutan. Sistem manajemen basis data (SMBD) pada umumnya menyediakan fungsi-fungsi server basis data, dan beberapa SMBD (seperti halnya MySQL atau Microsoft SQL Server) sangat bergantung kepada model klien-server untukmengakses basis datanya.Legenda Terbentuknya Istilah DatabaseIstilah “database” berawal dari ilmu komputer. Meskipun kemudianartinya semakin luas, memasukkan hal-hal di luar bidang elektronika, artikel inimengenai database komputer. Catatan yang mirip dengan database sebenarnyasudah ada sebelum revolusi industri yaitu dalam bentuk buku besar, kuitansi dan kumpulan data yang berhubungan dengan bisnisJenis DatabaseTerdapat 12 tipe database, antara lainOperational database,Analytical database,Data warehouse,Distributed database,End-user database,External database,Hypermedia databases on the web,Navigational database,In-memory databases,Document-oriented databases,Real-time databases,danRelational Database.Kata Kunci : Kapasitas Server Dan Data Base

EXTERNAL DATABASE SEBAGAI MEDIA INTEGRASI SISTEM INFORMASI AKADEMIK DENGAN E-LEARNING

Universitas Bina Darma Palembang merupakan salah satu Perguruan Tinggi Swasta yang memiliki banyak fakultas dan program studi. Untuk mengelola data akademik seperti penjadwalan, matakuliah, krs dan khs Universitas Bina Darma suda menggunakan Sistem Informasi Akademik yang sudah terintegrasi. Untuk mendukung proses belajar mengajar Universitas Bina Darma juga telah menggunakan Learning Management System (LMS) berbasis Moodle. Selama ini proses pengiriman data user, kelas, dan peserta kelas dilakukan dengan membuat program transfer data yang akan mentransfer data dari SIA ke Moodle. Permasalahan yang timbul adalah pertama jika ada perubahan data user seperti password dan lain sebagainya pada pertengahan semester maka tidak bisa secara otomatis mensikron dari SIA ke Moodle, sama halnya dengan perubahan data pengajar atau peserta kelas pada pertengahan semester harus dilakukan secara manual pada moodle, kedua riwayat peserta kelas dan pengajarnyapun terhapus setiap semester, karena program tersebut mengosongkan data kelas dan pesertanya setiap semester, hal ini menyebabkan dosen harus membackup dan mengupload ulang materi dan tugas nya setiap semester. Mengatasi hal tersebut dengan metode action research penulis membuat penelitian “External Database Sebagai Media Integrasi Sistem Informasi Akademik dengan Elaerning” sebagai solusinya. Penggunaan fitur External Database mengintegrasikan SIA dengan Moodle secara realtime, dan juga bisa mempertahankan riwayat mengajar dosen dan peserta kelas