Leukemia is a fatal cancer and has two main types: Acute chronic. Each type more subtypes: Lymphoid myeloid. Hence, in total, there are four subtypes of leukemia. This study proposes new approach for diagnosis all leukemia from microscopic blood cell images using convolutional neural networks (CNN), which requires large training data set. Therefore, we also investigated the effects augmentation an increasing number samples synthetically. We used publicly available sources: ALL-IDB ASH Image...

Abstract Drugs bind to their target proteins, which interact with downstream effectors and ultimately perturb the transcriptome of a cancer cell. These perturbations reveal information about source, i.e., drugs’ targets. Here, we investigate whether these protein interaction networks can uncover drug targets key pathways. We performed first systematic analysis over 500 drugs from Connectivity Map. First, show that gene expression is usually not significantly affected by perturbation. Hence,...

Alzheimer's disease is a brain that causes impaired cognitive abilities in memory, concentration, planning, and speaking. defined as the most common cause of dementia changes different parts brain. Neuroimaging, cerebrospinal fluid, some protein abnormalities are commonly used clinical diagnostic biomarkers. In this study, neuroimaging biomarkers were applied for diagnosis noninvasive method. Structural magnetic resonance (MR) images input predictive model. T1 weighted volumetric MR reduced...

Abstract Metastatic colorectal cancer (CRC) is still in need of effective treatments. This study applies a holistic approach to propose new targets for treatment primary and liver metastatic CRC investigates their therapeutic potential in-vitro. An integrative analysis samples was implemented alternative target proposals. Integrated microarray were grouped based on co-expression network analysis. Significant gene modules correlated with phenotypes identified. Network clustering pathway...

Combining omics data from different layers using integrative methods provides a better understanding of the biology complex disease such as cancer. The discovery biomarkers related to cancer development or prognosis helps find more effective treatment options. This study integrates multi-omics types with network-based approach explore common gene modules among tumors by running community detection on integrated network. were evaluated several biological metrics adapted Then, new prognostic...

Disease progression in cancer can vary substantially between patients. Yet, patients often receive the same treatment. Recently, there has been much work on predicting disease and patient outcome variables from gene expression order to personalize treatment options. Despite first diagnostic kits market, are open problems such as choice of random signatures or noisy data. One approach deal with these two employs protein–protein interaction networks ranks genes using surfer model Google’s...

With the developing technology, number of comments made on internet is increasing day by day. It has become almost impossible to make a manual sentiment analysis these comments. Therefore, new algorithms should be developed automatically perform texts. In this study, model been for Turkish While model, lexicon-based methods and machine learning were used together. As naïve method analysis, root each word in sentence takes score from dictionary final polarity relevant calculated using...

During a cell state transition, cells travel along trajectories in gene expression space. This dynamical systems framework complements the traditional concept of molecular pathways that drive phenotype switching. To expose structure hinders cancer from exiting robust proliferative state, we assessed perturbation capacity drug library and identified 16 non-cytotoxic compounds stimulate MCF7 breast to exit differentiated state. The transcriptome triggered by these drugs diverged, then...

Machine-Learning (ML) methods are applied to diagnose diseases and observe disease developments. We utilized several ML on Z-Alizadeh Sani dataset, which is about Coronary Artery Disease (CAD). t-test for feature selection then Principal Component Analysis (PCA) reduce dimensionality because of small sample size. 10-fold Cross-Validation was methods, achieved higher than 80% average accuracy. Besides, sensitivity specificity results around 70% 90%, respectively. The Artificial Neural Network...

Stock market forecasting is a challenging problem. In order to cope with this problem, various techniques and methods have been proposed. study, the stock close values are tried be forecasted as monthly weekly. For purpose, of two traded stocks (Google, Amazon) predicted using models being processed. addition, data were taken from different indexes (Dow Jones Industrial Average (DJIA) S&P 500) for realistic assumption. includes long term dependencies. reason, classical Recurrent Neural...

Rye (Secale cereale) is an important diploid (2n = 14, RR) crop species of the Triticeae and a better understanding its organellar genome variation can aid in improvement. Previous genetic analyses rye focused on nuclear genome. In present study, objective was to investigate diversity relationships 96 accessions representing diverse geographic regions using chloroplast (cp) mitochondrial (mt) DNA PCR-RFLPs. Seven cpDNA 4 mtDNA coding noncoding were amplified universal primer pairs. Each...

Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially in vitro experiments. To accelerate the synergistic discovery process, we present a new classification model to identify more anti-cancer pairs using silico network biology approach. Based on hypotheses that synergy comes from collective effects biological network, therefore, developed six features, including overlap distance perturbation were derived by individual...

Determination of cell signalling behaviour is crucial for understanding the physiological response to a specific stimulus or drug treatment. Current approaches large-scale data analysis do not effectively incorporate critical topological information provided by network. We herein describe novel model- and data-driven hybrid approach, signal transduction score flow algorithm, which allows quantitative visualization cyclic pathways that lead ultimate responses such as survival, migration...

This study applies personality prediction of a Twitter user based on the words used in tweets posted by user. The type is predicted Big Five Personality Model that outputs agreeableness, conscientiousness, openness, neuroticism, and extraversion as traits. We analyzed Turkish for prediction, prepared new dictionary includes with their special word groups. most successful machine learning methods are selected to predict each trait. When models were trained latest 50 users, estimated trait...

Yeni baştan ilaç geliştirme, karmaşık ve oldukça pahalı bir süreçtir. Bu nedenle, son yıllarda yeni hesaplamalı yaklaşımlar geliştirilmiştir. Hesaplamalı yaklaşımlardan biri, onaylanmış ilaçlara tedavi alanını keşfeden yeniden konumlandırmadır. Çünkü konumlandırma, geleneksel geliştirme süreçlerine kıyasla daha düşük maliyet, kısa süre risksiz yatırım sağlamaktadır. Son zamanlarda, biyolojik ağ tabanlı proteinler arasındaki fiziksel ilişkileri veya işlevsel benzerlikleri kullandığı sonunda...

Characterizing all possible side effects of compounds is not a trivial task due to unknown off-target proteins that might eventually lead lethal reactions. There still tremendous need computational methods identify protein targets new compound. We have performed comprehensive analysis for identification by integrating tissue-specific protein-protein interaction (PPI) networks and compound induced transcriptome data. Several network centrality metrics are computed suggest the most probable...

Diagnosis in the early phases of many diseases makes it possible to treat disease and affects treatment process positively. This is especially important for like Alzheimer field neurology. The use a computerized support system, which can autonomously perform diagnostic by expert this process, saves time helps reduce most human errors. In study, machine learning models with ability diagnose dementia Alzheimer's were developed predicting Clinical Dementia Rating (CDR) value. Artificial Neural...