How is information encoded in dna

To ensure that fragments of DNA are made at relatively similar lengths, the team added an enzyme that degrades DNA and stops chains from elongating beyond the desired average length. This is important to get consistent pools of DNA that are read with similar efficiency when it is time to decode the data. Furthermore, the team used nanopore sequencing, which allows for user-defined allocation of sequencing depth and data recovery.

This approach reduces reagent use and data volume to get the same information at a fraction of the cost. Both de novo enzymatic DNA synthesis and nanopore sequencing could help reduce costs associated with the use of DNA for the storage of digital information in practice. This strategy cuts in-house sequencing and synthesis costs. An advantageous byproduct of this all-in-one platform that further decreases costs is also the elimination of third-party synthetic DNA providers adopted by existing commercial DNA storage platforms.

The length of DNA fragments generated by the template-independent polymerase, known as TdT terminal deoxynucleotidyl transferase , is shorter than that of DNA fragments generated by the more commonly used phosphoramidite chemistry, and researchers will still have to figure out how this might limit the encoded volume of information.

Studies thus far have reported smaller scale hundreds of bits of encoded information encoding in short DNA fragment pools. It is true that decades of intense study have given researchers a detailed understanding of particular characteristics—the phenotypes—of cells and tissues that have been altered by disease. And in recent years, dramatic progress in gene sequencing has made it possible for scientists to make correlations between these phenotypes and specific genes.

But the complex network of interactions lying between the two is largely unknown. This is the realm of biomedical data science, the use of quantitative methods and large datasets to trace basic physiological processes. Assistant Professor of Biomedical Engineering Mete Civelek uses big data analytics to understand the molecular pathways of disease and develops personalized medicine approaches to cardiovascular and metabolic disorders. Civelek and his lab at the University of Virginia combine a variety of statistical, computational and experimental methods to track the cascade of biological events that ultimately yields a particular disease phenotype.

In the case of diabetes, they used bioinformatic approaches to predict that a variant of a gene in a specific region of chromosome 7 decreases the production of a protein, KLF This protein, in turn, regulates the function of fat cells.

But these LDOs can operate only in a particular window of voltage. For example, if the supply voltage that would be most efficient for the core is 0. Similarly, if V IN has already been set below a certain voltage limit, the LDO's analog components won't work properly and the circuit can't be engaged to reduce the core supply voltage further.

The main obstacle that has limited use of digital LDOs so far is the slow transient response. However, if the desired voltage falls inside the LDO's window, software enables the circuit and activates a reference voltage equal to the target supply voltage.

In the basic analog LDO design, it's by means of an operational amplifier, feedback, and a specialized power p -channel field effect transistor PFET. The latter is a transistor that reduces its current with increasing voltage to its gate. The op amp continuously compares the circuit's output voltage—the core's supply voltage, or V DD —to the target reference voltage. If the LDO's output voltage falls below the reference voltage—as it would when newly active logic suddenly demands more current—the op amp reduces the power PFET's gate voltage, increasing current and lifting V DD toward the reference voltage value.

Conversely, if the output voltage rises above the reference voltage—as it would when a core's logic is less active—then the op amp increases the transistor's gate voltage to reduce current and lower V DD. The LDO also has its own clock circuit, separate from those used by the processor core.

With each tick of the clock, the comparator measures whether the output voltage is below or above the target voltage provided by the reference source. The comparator output guides the control logic in determining how many of the power PFETs to activate.

Their combined current props up the core's supply voltage, and that value feeds back to the comparator to keep it on target. If it overshoots, the comparator signals to the control logic to switch some of the PFETs off.

The key advantage of an analog design is that it can respond rapidly to transient droops and overshoots in the supply voltage, which is especially important when those events involve steep changes. These transients occur because a core's demand for current can go up or down greatly in a matter of nanoseconds. In addition to the fast response, analog LDOs are very good at suppressing variations in V IN that might come in from the other cores on the rails. And, finally, when current demands are not changing much, it controls the output tightly without constantly overshooting and undershooting the target in a way that introduces ripples in V DD.

When a core's current requirement changes suddenly it can cause the LDO's output voltage to overshoot or droop [top]. Basic digital LDO designs do not handle this well [bottom left]. However, a scheme called adaptive sampling with reduced dynamic stability [bottom right] can reduce the extent of the voltage excursion. It does this by ramping up the LDO's sample frequency when the droop gets too large, allowing the circuit to respond faster.

Source: S. Nasir et al. These attributes have made analog LDOs attractive not just for supplying processor cores, but for almost any circuit demanding a quiet, steady supply voltage. However, there are some critical challenges that limit the effectiveness of these designs.

First analog components are much more complex than digital logic, requiring lengthy design times to implement them in advanced technology nodes.

And finally, the dropout voltage of analog LDOs isn't as small as designers would like. Taking those last points together, analog LDOs offer a limited voltage window at which they can operate. That means there are missed opportunities to enable LDOs for power saving—ones big enough to make a noticeable difference in a smartphone's battery life.

Digital LDOs undo many of these weaknesses: With no complex analog components, they allow designers to tap into a wealth of tools and other resources for digital design. So scaling down the circuit for a new process technology will need much less effort.

Digital LDOs will also operate over a wider voltage range. At the low-voltage end, the digital components can operate at V IN values that are off-limits to analog components. And in the higher range, the digital LDO's dropout voltage will be smaller, resulting in meaningful core-power savings.

But nothing's free, and the digital LDO has some serious drawbacks. Most of these arise because the circuit measures and alters its output only at discrete times, instead of continuously. That means the circuit has a comparatively slow response to supply voltage droops and overshoots.

It's also more sensitive to variations in V IN , and it tends to produce small ripples in the output voltage, both of which could degrade a core's performance. It might seem straightforward that low-dropout voltage regulators LDOs could minimize processor power consumption by allowing cores to run at a variety of power levels, but exactly how do they do that? The total power consumed by a core is simply the product of the supply voltage and the current through that core.

But voltage and current each have both a static component and a dynamic one—dependent on how frequently transistors are switching. The core current's static component is made up of the current that leaks across devices even when the transistors are not switching and is dependent on supply voltage. Its dynamic component, on the other hand, is a product of capacitance, clock frequency, and supply voltage. For a core connected directly to a voltage rail supplied by the external power supply IC, lowering V IN results in a quadratic reduction in dynamic power with respect to frequency plus a static power reduction that depends on the sensitivity of leakage current to V IN.

So lowering the rail voltage saves quite a lot. At a minimum, that's the product of the voltage across the LDO the eponymous dropout voltage in the circuit's name and the core current.

When you factor that in, the dynamic power saving from lowering the voltage is a linear relation to supply voltage rather than the quadratic one you get without the LDO. Even so, using an LDO to scale supply voltage is worthwhile. Of these, the main obstacle that has limited the use of digital LDOs so far is their slow transient response.

Cores experience droops and overshoots when the current they draw abruptly changes in response to a change in its workload. The LDO response time to droop events is critical to limiting how far voltage falls and how long that condition lasts. Conventional cores add a safety margin to the supply voltage to ensure correct operation during droops. A greater expected droop means the margin must be larger, degrading the LDO's energy-efficiency benefits. So, speeding up the digital LDO's response to droops and overshoots is the primary focus of the cutting-edge research in this field.

One approach uses the digital LDO's clock frequency as a control knob to trade stability and power efficiency for response time.