Sequence Properties
Sequence Properties - Related Videos
08:57
Amplicon Sequencing using the Long-Read Sequencing Technologies
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2025
This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.
02:57
Physical and Chemical Properties of Matter
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2020
The characteristics that enable us to distinguish one substance from another are called properties. Physical Properties of Matter A physical property is a characteristic of matter that is not associated with a change in its chemical composition. Familiar examples of physical properties include density, color, hardness, melting and boiling points, and electrical conductivity. We can observe some physical properties, such as density and color, without changing the physical state of the matter...
02:58
Properties of Transition Metals
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2020
Transition metals are defined as those elements that have partially filled d orbitals. As shown in Figure 1, the d-block elements in groups 3–12 are transition elements. The f-block elements, also called inner transition metals (the lanthanides and actinides), also meet this criterion because the d orbital is partially occupied before the f orbitals. Figure 1: Periodic Table. The transition metals are located in groups 3–11 of the periodic table. The inner transition metals are in the two rows...
07:30
Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
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Cited by 19 •
2020
This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.
02:02
Cis-regulatory Sequences
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2020
Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
FAQs
Monotonicity is tested by comparing neighboring terms, often through the difference a_(n+1) - a_n or the ratio of successive terms when that comparison is appropriate. Nonnegative differences indicate a nondecreasing sequence, while nonpositive differences indicate a nonincreasing one. This sign pattern reveals directional behavior without requiring the entire sequence to be listed.
Boundedness and convergence describe different aspects of behavior. A bounded sequence remains within fixed upper and lower limits, whereas convergence requires its terms to approach one finite value. Thus, checking bounds can show that growth is restricted, but a separate limit argument may be needed to decide whether the sequence settles or continues to oscillate.
Periodicity is identified when a fixed block of terms repeats after a constant index interval. That repeated pattern differs from convergence: unless the repeating values effectively reduce to one value, the sequence does not approach a single limit. Comparing the period with observed oscillations therefore helps distinguish structured repetition from nonrepeating fluctuations or directional growth.
To analyze an unfamiliar sequence, first write several terms from its explicit formula or recurrence relation, then compare successive values for monotonicity and inspect whether they remain within bounds. Next, examine the limiting behavior, including possible oscillation or unbounded growth, and check for a repeating interval. This workflow connects visible patterns with formal properties.
In numerical approximation, sequence properties indicate whether repeated calculations are moving toward a stable value. Convergence supports using later terms as approximations, while divergence or persistent oscillation warns that iteration may not settle. Examining boundedness and successive changes helps evaluate the reliability of an iterative process before treating a computed term as an accurate result.
Sequence properties provide a framework for studying infinite series because the terms and their partial sums can be examined for limiting behavior. They also support analysis of algorithms and mathematical models, where repeated updates generate successive values. In these settings, monotonicity, bounds, and convergence help describe long-run performance and determine whether calculations remain controlled.