Statistical Sciences / Computer Applications & Bioinformatics / Full Subject

40 Qs Overview

Computer Applications & Bioinformatics

Official Statistical Sciences Computer Applications & Bioinformatics complete subject practice test — All questions across all syllabus chapters.

Q.11

ICAR 2023Shift 1 MCQ (Single Correct) +4 −1

What is the primary objective of bioinformatics?

जैव सूचना विज्ञान (बायोइन्फॉर्मेटिक्स) का प्राथमिक उद्देश्य क्या है?

To develop new drugs and therapies नई औषधियां एवं उपचार विकसित करना To study the structure and function of molecules अणुओं की संरचना और कार्य का अध्ययन करना To analyze and interpret biological data using computational tools कंप्यूटेशनल उपकरणों का उपयोग करके जैविक डेटा का विश्लेषण और व्याख्या करना To design and engineer new biological systems नए जैविक तंत्रों का डिजाइन और निर्माण करना

Q.12

ICAR 2024Shift 1 MCQ (Single Correct) +4 −1

A polymorphic virus can:

एक बहुरूपी वायरस (Polymorphic virus) कर सकता है:

Spreading through social media platforms सोशल मीडिया प्लेटफॉर्म के माध्यम से फैलना Change its appearance अपना रूप / बाह्य स्वरूप बदलना Deleting files randomly फाइलों को यादृच्छिक रूप से हटाना Only infecting specific file types केवल विशिष्ट फ़ाइल प्रकारों को संक्रमित करना

A polymorphic virus is a complex malicious computer program that changes its binary signature and code appearance every time it infects a new system or file, typically using different encryption keys and decryptor routines.

Why Option 2 is correct: Polymorphic viruses are specifically engineered to change their appearance (underlying code and decryption routine) with each iteration while preserving their core functionality, thereby evading signature-based antivirus scanners.
Other options: Spreading across platforms or deleting files are general malware activities, but changing code appearance is the defining characteristic of polymorphism.

एक बहुरूपी वायरस (Polymorphic virus) ऐसा मैलवेयर है जो हर संक्रमण के साथ अपनी कोड संरचना और बाह्य स्वरूप (appearance/signature) को बदल लेता है ताकि एंटीवायरस सॉफ्टवेयर उसे पहचान न सके।

विकल्प 2 सही क्यों है: यह वायरस अलग-अलग एन्क्रिप्शन कुंजियों और डिक्रिप्टर रूटीन का उपयोग करके हर बार अपनी पहचान बदलता है, जिससे पारंपरिक सिग्नेचर-आधारित स्कैनर्स इसे नहीं पकड़ पाते।

अतः विकल्प 2 सही उत्तर है।

Explanation not matching this question? क्या व्याख्या इस प्रश्न से मेल नहीं खा रही? Report

Q.13

ICAR 2024Shift 1 MCQ (Single Correct) +4 −1

Execution of two or more programs by a single CPU is known as:

एकल सीपीयू (single CPU) द्वारा दो या दो से अधिक प्रोग्रामों के निष्पादन को जाना जाता है:

Multiprogramming मल्टीप्रोग्रामिंग Multiprocessing मल्टीप्रोसेसिंग Timesharing टाइमशेयरिंग CPU Sharing सीपीयू शेयरिंग

Q.14

ICAR 2023Shift 1 MCQ (Single Correct) +4 −1

Which of the following is not a bioinformatics tool ?

निम्नलिखित में से कौन-सा जैव सूचना विज्ञान उपकरण (Bioinformatics tool) नहीं है?

BLAST BLAST ClustalW ClustalW PCR PCR Phylip Phylip

Analysis of bioinformatics versus wet-lab techniques:

Incorrect (Is a tool): BLAST is a widely used heuristic sequence alignment search program.
Incorrect (Is a tool): ClustalW is a standard bioinformatics tool for multiple sequence alignment.
Correct (Not a tool): PCR (Polymerase Chain Reaction) is an in vitro wet-laboratory molecular biology technique used to amplify specific DNA fragments enzymaticallly, not a computational bioinformatics software tool.
Incorrect (Is a tool): PHYLIP (Phylogeny Inference Package) is a bioinformatics software package for inferring evolutionary trees.

जैव सूचना विज्ञान बनाम प्रायोगिक तकनीकों का विश्लेषण:

गलत (उपकरण है): BLAST अनुक्रम संरेखण का सॉफ्टवेयर उपकरण है।
गलत (उपकरण है): ClustalW बहु-अनुक्रम संरेखण (Multiple sequence alignment) का मानक उपकरण है।
सही (उपकरण नहीं है): पीसीआर (Polymerase Chain Reaction - PCR) प्रयोगशाला में डीएनए प्रवर्धन (DNA amplification) की एक जैव रासायनिक / आण्विक तकनीक है, कोई कम्प्यूटेशनल सॉफ्टवेयर उपकरण नहीं।
गलत (उपकरण है): PHYLIP फाइलोजेनेटिक विश्लेषण का सॉफ्टवेयर पैकेज है।

Explanation not matching this question? क्या व्याख्या इस प्रश्न से मेल नहीं खा रही? Report

Q.15

ICAR 2023Shift 1 MCQ (Single Correct) +4 −1

Which of the following is not an example of DBMS?

निम्नलिखित में से कौन-सा डेटाबेस प्रबंधन प्रणाली का उदाहरण नहीं है?

MySQL MySQL Microsoft Access माइक्रोसॉफ्ट एक्सेस IBM DB2 IBM DB2 Google गूगल

General Agriculture, Economics & Extension

8 Topics

Agronomy, Agro-Climatic Zones, Cropping Systems, Tillage and Soil Fertility Management Major Plant Diseases, Insect Pests, Weeds and Integrated Pest Management (IPM) Plant Physiology, Mineral Nutrition, Genetics and Plant Breeding Fundamentals Historical Milestones, Agricultural Research Infrastructure and ICAR Institutes Micro & Macro Economics: Demand, Supply, Production Costs and Market Structures Agricultural Marketing, Market Intermediaries, Price Policy, MSP and Buffer Stocking Agricultural Finance, Credit Institutions (NABARD, RRBs, Commercial Banks) and KCC Extension Education Principles, Rural Development Programs and Community Reconstruction

Mathematics

9 Topics

Differential Calculus: Limits, Continuity, Differentiability, Successive Differentiation and Expansion of Functions Sequences and Series: Arithmetic, Geometric, Harmonic Progressions and Infinite Series Convergence Matrices and Determinants: Matrix Operations, Rank, Inverse, Systems of Linear Equations and Eigenvalues Sets, Relations, Functions, Mathematical Induction and Theory of Equations Integral Calculus: Definite and Indefinite Integrals, Reduction Formulas and Areas Under Curves Differential Equations: First Order Ordinary Differential Equations, Linear Differential Equations with Constant Coefficients Applications of Derivatives: Tangents, Normals, Maxima-Minima, Mean Value Theorems and Indeterminate Forms Numerical Methods: Interpolation, Numerical Differentiation, Integration (Trapezoidal, Simpson) and Root Finding Coordinate Geometry: Straight Lines, Circles, Parabola, Ellipse and Hyperbola in Two Dimensions

Statistical Methods & Experimental Designs

14 Topics

Theoretical Discrete Probability Distributions: Bernoulli, Binomial, Poisson, Geometric and Hypergeometric Design of Experiments: Principles of Experimentation, CRD, RBD, Latin Square Design (LSD) and Factorial Experiments Probability Theory: Classical, Axiomatic Definitions, Addition, Multiplication Theorems and Bayes Theorem Small Sample Tests: Students t-test, Snedecors F-test, Chi-Square Test of Goodness of Fit and Contingency Tables Measures of Central Tendency: Arithmetic Mean, Geometric Mean, Harmonic Mean, Median and Mode Theoretical Continuous Probability Distributions: Uniform, Normal, Exponential, Beta and Gamma Distributions Sampling Theory: Census vs Sample Survey, Sampling Errors, SRSWOR, SRSWR, Stratified, Systematic and Cluster Sampling Measures of Dispersion: Range, Quartile Deviation, Mean Deviation, Standard Deviation and Coefficient of Variation Testing of Hypotheses: Null and Alternative Hypotheses, Type I and II Errors, Significance Level, Large Sample Tests (Z-test) Collection, Classification and Tabulation of Data, Frequency Distributions and Graphical Representations Regression Analysis: Simple and Multiple Linear Regression, Least Squares Principle, Properties and R-Squared Random Variables, Probability Mass and Density Functions, Expectation and Moment Generating Functions Correlation Analysis: Simple, Partial, Multiple Correlation, Pearson Coefficient and Rank Correlation Moments, Skewness (Karl Pearson, Bowley) and Kurtosis