Efficient Feature Selection and Classification of Protein Sequence Data in Bioinformatics

Bioinformatics has been an emerging area of research for the last three decades. The ultimate aims of bioinformatics were to store and manage the biological data, and develop and analyze computational tools to enhance their understanding. The size of data accumulated under various sequencing projects is increasing exponentially, which presents difficulties for the experimental methods. To reduce the gap between newly sequenced protein and proteins with known functions, many computational techniques involving classification and clustering algorithms were proposed in the past. The classification of protein sequences into existing superfamilies is helpful in predicting the structure and function of large amount of newly discovered proteins. The existing classification results are unsatisfactory due to a huge size of features obtained through various feature encoding methods. In this work, a statistical metric-based feature selection technique has been proposed in order to reduce the size of the extracted feature vector. The proposed method of protein classification shows significant improvement in terms of performance measure metrics: accuracy, sensitivity, specificity, recall, F-measure, and so forth

EEG Channel Selection Techniques in Motor Imagery Applications: A Review and New Perspectives

Communication, neuro-prosthetics, and environmental control are just a few applications for disabled persons who use robots and manipulators that use brain-computer interface (BCI) systems. The brain’s motor imagery (MI) signal is an essential input for a brain-related task in BCI applications. Due to their noninvasive, portability, and cost-effectiveness, electroencephalography (EEG) signals are the most widely used input in BCI systems. The EEG data are often collected from more than 100 different locations in the brain; channel selection techniques are critical for selecting the optimum channels for a given application. However, when analyzing EEG data, the principal purpose of channel selection is to reduce computational complexity, improve classification accuracy by avoiding overfitting, and reduce setup time. Several channel selection assessment algorithms, both with and without classification-based methods, extracted appropriate channel subsets using defined criteria. Therefore, based on the exhaustive analysis of the EEG channel selection, this manuscript analyses several existing studies to reduce the number of noisy channels and improve system performance. We review several existing works to find the most promising MI-based EEG channel selection algorithms and associated classification methodologies on various datasets. Moreover, we focus on channel selection methods that choose fewer channels with great precision. Finally, our main finding is that a smaller channel set, typically 10–30% of total channels, provided excellent performance compared to other existing studies

Acute mesenteric ischemia: A case report

Acute mesenteric ischemia is a rare life-threatening diagnostic and therapeutic emergency. Lack of clinical and biological specificity makes the diagnosis difficult. Imaging, particularly computed tomography can help confirm the diagnosis. An underlying cause is identified in about 30%-70% of cases and should always be sought. We report a case of a 51-year-old man with chronic alcoholic liver disease admitted to the emergency department for abdominal pain. Computed tomography showed mesenteric venous thrombosis with signs of small bowel ischemia and cirrhosis with portal hypertension. Through this observation, we describe the imaging aspects of mesenteric ischemia and emphasize the necessity of seeking underlying pathological condition

Pylephlebitis complicating acute calculous cholecystitis: A case report

Pylephlebitis is a complication of intra-abdominal infections. Its occurrence during cholecystitis is a rare situation. We report the case of a 43-year-old female patient who presented with septic thrombosis of the right portal branch following acute calculous cholecystitis diagnosed on abdominal CT. The clinical evolution was favorable under antibiotic therapy and a cholecystectomy was scheduled

Case report of a lithopedion of tubal location, in a young woman

Lithopedion is a rare situation, corresponding to an ectopic pregnancy which evolves beyond the first trimester toward death and fetal calcification. This ectopic pregnancy is most often abdominal in location. Through this case report, we report the case of a lithopedion of left tubal localization in a young woman, diagnosed on CT scan following abdominal pain and confirmed by laparotomy with excision

Small bowel obstruction due to congenital band in an adult: Radio-surgical correlation

Congenital band is a rare cause of bowel obstruction, most commonly occurring in childhood. We report a case of a young adult with no medical and surgical previous history who had symptoms of bowel obstruction evolving for 2 days. Computed tomography (CT) found an adhesive band causing a small bowel obstruction. An open laparotomy was performed, and the intraoperative findings were consistent with a congenital band compressing the ileum. Through this clinical case, we illustrate an uncommon cause of bowel obstruction and the interest of the CT for the management

Atypical fibromuscular dysplasia or carotid web revealed by cerebral infarction: A review of 2 cases

Atypical fibromuscular dysplasia of the bulb or carotid web is a nonatheromatous pathology more common in African and African-American populations. It is implicated in the occurrence of cerebral infarcts of unknown causes. Its diagnosis is made by angio-CT of the supra-aortic trunks and is characterized by a defect in the posterior wall of the bulb. Treatment with antiplatelet agents prevents the occurrence of stroke, but radical treatment remains surgical and endovascular. We report 2 observations of carotid web diagnosed and medically managed at the regional hospital of Saint Louis